diff --git a/.github/workflows/build_and_test.yml b/.github/workflows/build_and_test.yml
index 8a80dd519..67246b344 100644
--- a/.github/workflows/build_and_test.yml
+++ b/.github/workflows/build_and_test.yml
@@ -37,7 +37,7 @@ jobs:
         run: uv run python3 -m pytest --runslow .
 
       - name: Check Python Types
-        run: uvx ty check
+        run: uv run ty check
 
       - name: Build Core
         run: uv build
diff --git a/.github/workflows/format_and_lint.yml b/.github/workflows/format_and_lint.yml
index e1d6aabc8..c81156cf8 100644
--- a/.github/workflows/format_and_lint.yml
+++ b/.github/workflows/format_and_lint.yml
@@ -40,12 +40,12 @@ jobs:
 
       - name: Lint with ruff
         run: |
-          uvx ruff check
+          uv run ruff check
 
       - name: Format with ruff
         run: |
-          uvx ruff format --check .
+          uv run ruff format --check .
 
       - name: Typecheck with ty
         run: |
-          uvx ty check
+          uv run ty check
diff --git a/.gitignore b/.gitignore
index a4b8f5f71..ce76a0841 100644
--- a/.gitignore
+++ b/.gitignore
@@ -21,3 +21,5 @@ libs/server/build
 dist/
 
 .mcp.json
+
+test_output/
diff --git a/app/desktop/WinInnoSetup.iss b/app/desktop/WinInnoSetup.iss
index 085633dc3..d9c0b14d6 100644
--- a/app/desktop/WinInnoSetup.iss
+++ b/app/desktop/WinInnoSetup.iss
@@ -3,7 +3,7 @@
 
 #define MyAppPath "build\dist\Kiln"
 #define MyAppName "Kiln"
-#define MyAppVersion "0.24.0"
+#define MyAppVersion "0.25.0"
 #define MyAppPublisher "Chesterfield Laboratories Inc"
 #define MyAppURL "https://kiln.tech"
 #define MyAppExeName "Kiln.exe"
diff --git a/app/desktop/pyproject.toml b/app/desktop/pyproject.toml
index 3f8a06ead..1de7056d5 100644
--- a/app/desktop/pyproject.toml
+++ b/app/desktop/pyproject.toml
@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "kiln-studio-desktop"
-version = "0.24.0"
+version = "0.25.0"
 description = "The Kiln Desktop App. Download from https://kiln.tech"
 requires-python = ">=3.10"
 dependencies = [
diff --git a/app/desktop/studio_server/test_copilot_api.py b/app/desktop/studio_server/test_copilot_api.py
index 19fa0822a..e9982a232 100644
--- a/app/desktop/studio_server/test_copilot_api.py
+++ b/app/desktop/studio_server/test_copilot_api.py
@@ -13,11 +13,13 @@
 from app.desktop.studio_server.copilot_api import connect_copilot_api
 from fastapi import FastAPI
 from fastapi.testclient import TestClient
+from kiln_server.custom_errors import connect_custom_errors
 
 
 @pytest.fixture
 def app():
     app = FastAPI()
+    connect_custom_errors(app)
     connect_copilot_api(app)
     return app
 
@@ -123,7 +125,7 @@ def test_clarify_spec_no_api_key(self, client, clarify_spec_input):
 
             response = client.post("/api/copilot/clarify_spec", json=clarify_spec_input)
             assert response.status_code == 401
-            assert "API key not configured" in response.json()["detail"]
+            assert "API key not configured" in response.json()["message"]
 
     def test_clarify_spec_success(self, client, clarify_spec_input, mock_api_key):
         mock_output = MagicMock(spec=ClarifySpecOutput)
@@ -194,7 +196,7 @@ def test_clarify_spec_no_response(self, client, clarify_spec_input, mock_api_key
         ):
             response = client.post("/api/copilot/clarify_spec", json=clarify_spec_input)
             assert response.status_code == 500
-            assert "Failed to analyze spec" in response.json()["detail"]
+            assert "Failed to analyze spec" in response.json()["message"]
 
     def test_clarify_spec_validation_error(
         self, client, clarify_spec_input, mock_api_key
@@ -210,7 +212,7 @@ def test_clarify_spec_validation_error(
         ):
             response = client.post("/api/copilot/clarify_spec", json=clarify_spec_input)
             assert response.status_code == 422
-            assert "Validation error from server" in response.json()["detail"]
+            assert "Validation error from server" in response.json()["message"]
 
 
 class TestRefineSpec:
@@ -223,7 +225,7 @@ def test_refine_spec_no_api_key(self, client, refine_spec_input):
 
             response = client.post("/api/copilot/refine_spec", json=refine_spec_input)
             assert response.status_code == 401
-            assert "API key not configured" in response.json()["detail"]
+            assert "API key not configured" in response.json()["message"]
 
     def test_refine_spec_success(self, client, refine_spec_input, mock_api_key):
         mock_output = MagicMock(spec=RefineSpecApiOutput)
@@ -259,7 +261,7 @@ def test_refine_spec_no_response(self, client, refine_spec_input, mock_api_key):
         ):
             response = client.post("/api/copilot/refine_spec", json=refine_spec_input)
             assert response.status_code == 500
-            assert "Failed to refine spec" in response.json()["detail"]
+            assert "Failed to refine spec" in response.json()["message"]
 
     def test_refine_spec_validation_error(
         self, client, refine_spec_input, mock_api_key
@@ -275,7 +277,7 @@ def test_refine_spec_validation_error(
         ):
             response = client.post("/api/copilot/refine_spec", json=refine_spec_input)
             assert response.status_code == 422
-            assert "Validation error from server" in response.json()["detail"]
+            assert "Validation error from server" in response.json()["message"]
 
 
 class TestGenerateBatch:
@@ -290,7 +292,7 @@ def test_generate_batch_no_api_key(self, client, generate_batch_input):
                 "/api/copilot/generate_batch", json=generate_batch_input
             )
             assert response.status_code == 401
-            assert "API key not configured" in response.json()["detail"]
+            assert "API key not configured" in response.json()["message"]
 
     def test_generate_batch_success(self, client, generate_batch_input, mock_api_key):
         mock_output = MagicMock(spec=GenerateBatchOutput)
@@ -328,7 +330,7 @@ def test_generate_batch_no_response(
                 "/api/copilot/generate_batch", json=generate_batch_input
             )
             assert response.status_code == 500
-            assert "Failed to generate synthetic data" in response.json()["detail"]
+            assert "Failed to generate synthetic data" in response.json()["message"]
 
     def test_generate_batch_validation_error(
         self, client, generate_batch_input, mock_api_key
@@ -346,4 +348,4 @@ def test_generate_batch_validation_error(
                 "/api/copilot/generate_batch", json=generate_batch_input
             )
             assert response.status_code == 422
-            assert "Validation error from server" in response.json()["detail"]
+            assert "Validation error from server" in response.json()["message"]
diff --git a/app/desktop/studio_server/test_data_gen_api.py b/app/desktop/studio_server/test_data_gen_api.py
index 4d6fec692..bc9e4f995 100644
--- a/app/desktop/studio_server/test_data_gen_api.py
+++ b/app/desktop/studio_server/test_data_gen_api.py
@@ -3,6 +3,7 @@
 import pytest
 from fastapi import FastAPI
 from fastapi.testclient import TestClient
+from kiln_server.custom_errors import connect_custom_errors
 from kiln_ai.datamodel import (
     DataSource,
     DataSourceType,
@@ -31,6 +32,7 @@
 @pytest.fixture
 def app():
     app = FastAPI()
+    connect_custom_errors(app)
     connect_data_gen_api(app)
     return app
 
diff --git a/app/desktop/studio_server/test_eval_api.py b/app/desktop/studio_server/test_eval_api.py
index 1e3d6befc..c6bc12059 100644
--- a/app/desktop/studio_server/test_eval_api.py
+++ b/app/desktop/studio_server/test_eval_api.py
@@ -15,6 +15,7 @@
 from fastapi import FastAPI, HTTPException
 from fastapi.responses import StreamingResponse
 from fastapi.testclient import TestClient
+from kiln_server.custom_errors import connect_custom_errors
 from kiln_ai.adapters.ml_model_list import ModelProviderName
 from kiln_ai.datamodel import (
     DataSource,
@@ -55,6 +56,7 @@
 @pytest.fixture
 def app():
     app = FastAPI()
+    connect_custom_errors(app)
     connect_evals_api(app)
     return app
 
@@ -189,7 +191,7 @@ def test_get_eval_not_found(client, mock_task, mock_task_from_id):
     response = client.get("/api/projects/project1/tasks/task1/eval/non_existent")
 
     assert response.status_code == 404
-    assert response.json()["detail"] == "Eval not found. ID: non_existent"
+    assert response.json()["message"] == "Eval not found. ID: non_existent"
 
 
 @pytest.fixture
@@ -513,7 +515,7 @@ async def test_run_eval_config_no_run_configs_error(
 
         assert response.status_code == 400
         assert (
-            response.json()["detail"]
+            response.json()["message"]
             == "No run config ids provided. At least one run config id is required."
         )
 
@@ -785,7 +787,7 @@ def test_update_run_config_prompt_name_no_prompt(
         json={"prompt_name": "New Name"},
     )
     assert response.status_code == 400
-    assert "no frozen prompt" in response.json()["detail"].lower()
+    assert "no frozen prompt" in response.json()["message"].lower()
 
 
 @pytest.fixture
@@ -1354,7 +1356,7 @@ def test_delete_eval_not_found(client):
 
     # Verify the response
     assert response.status_code == 404
-    assert response.json()["detail"] == "Eval not found. ID: nonexistent_eval"
+    assert response.json()["message"] == "Eval not found. ID: nonexistent_eval"
 
 
 async def test_create_eval_then_delete_on_spec_failure(
@@ -1477,7 +1479,7 @@ def test_update_eval_train_set_filter_id_when_already_set(
     assert response.status_code == 400
     assert (
         "Train set filter is already set and cannot be changed"
-        in response.json()["detail"]
+        in response.json()["message"]
     )
 
 
@@ -1527,7 +1529,7 @@ def test_update_eval_not_found(client):
         )
 
     assert response.status_code == 404
-    assert "Eval not found" in response.json()["detail"]
+    assert "Eval not found" in response.json()["message"]
 
 
 def test_update_eval_empty_request(client, mock_task_from_id, mock_eval, mock_task):
@@ -1759,7 +1761,7 @@ async def test_get_eval_progress_not_found(client, mock_task_from_id, mock_task)
 
         # Verify the response
         assert response.status_code == 404
-        assert response.json()["detail"] == "Eval not found. ID: non_existent"
+        assert response.json()["message"] == "Eval not found. ID: non_existent"
         mock_eval_from_id.assert_called_once_with("project1", "task1", "non_existent")
 
 
@@ -1810,7 +1812,7 @@ async def test_set_current_eval_config_not_found(
 
     # Verify the response
     assert response.status_code == 400
-    assert response.json()["detail"] == "Eval config not found."
+    assert response.json()["message"] == "Eval config not found."
 
 
 @pytest.mark.parametrize(
@@ -1901,7 +1903,7 @@ async def test_create_task_run_config_invalid_temperature_values(
         },
     )
     assert response.status_code == 422
-    error_detail = response.json()["detail"]
+    error_detail = response.json()["message"]
     assert "temperature must be between 0 and 2" in str(error_detail)
 
     # Test temperature above 2
@@ -1919,7 +1921,7 @@ async def test_create_task_run_config_invalid_temperature_values(
         },
     )
     assert response.status_code == 422
-    error_detail = response.json()["detail"]
+    error_detail = response.json()["message"]
     assert "temperature must be between 0 and 2" in str(error_detail)
 
 
@@ -1945,7 +1947,7 @@ async def test_create_task_run_config_invalid_top_p_values(
         },
     )
     assert response.status_code == 422
-    error_detail = response.json()["detail"]
+    error_detail = response.json()["message"]
     assert "top_p must be between 0 and 1" in str(error_detail)
 
     # Test top_p above 1
@@ -1963,7 +1965,7 @@ async def test_create_task_run_config_invalid_top_p_values(
         },
     )
     assert response.status_code == 422
-    error_detail = response.json()["detail"]
+    error_detail = response.json()["message"]
     assert "top_p must be between 0 and 1" in str(error_detail)
 
 
@@ -2226,7 +2228,7 @@ def test_get_eval_configs_score_summary_no_filter_id(
 
         assert response.status_code == 400
         assert (
-            response.json()["detail"]
+            response.json()["message"]
             == "No eval configs filter id set, cannot get eval configs score summary."
         )
         mock_eval_from_id.assert_called_once_with("project1", "task1", "eval1")
diff --git a/app/desktop/studio_server/test_finetune_api.py b/app/desktop/studio_server/test_finetune_api.py
index d10385ccc..73f69f9a4 100644
--- a/app/desktop/studio_server/test_finetune_api.py
+++ b/app/desktop/studio_server/test_finetune_api.py
@@ -4,6 +4,18 @@
 
 import httpx
 import pytest
+from app.desktop.studio_server.finetune_api import (
+    CreateDatasetSplitRequest,
+    CreateFinetuneRequest,
+    DatasetSplitType,
+    FinetuneProviderModel,
+    compute_finetune_tag_info,
+    connect_fine_tune_api,
+    data_strategies_from_finetune_id,
+    fetch_fireworks_finetune_models,
+    infer_data_strategies_for_model,
+    thinking_instructions_from_request,
+)
 from fastapi import FastAPI
 from fastapi.testclient import TestClient
 from kiln_ai.adapters.fine_tune.base_finetune import FineTuneParameter
@@ -39,21 +51,9 @@
     KilnAgentRunConfigProperties,
     ToolsRunConfig,
 )
+from kiln_server.custom_errors import connect_custom_errors
 from pydantic import BaseModel
 
-from app.desktop.studio_server.finetune_api import (
-    CreateDatasetSplitRequest,
-    CreateFinetuneRequest,
-    DatasetSplitType,
-    FinetuneProviderModel,
-    compute_finetune_tag_info,
-    connect_fine_tune_api,
-    data_strategies_from_finetune_id,
-    fetch_fireworks_finetune_models,
-    infer_data_strategies_for_model,
-    thinking_instructions_from_request,
-)
-
 
 @pytest.fixture
 def test_task(tmp_path):
@@ -173,6 +173,7 @@ def mock_task_from_id_disk_backed(test_task, monkeypatch):
 @pytest.fixture
 def client():
     app = FastAPI()
+    connect_custom_errors(app)
     connect_fine_tune_api(app)
     return TestClient(app)
 
@@ -391,7 +392,7 @@ def test_get_finetune_hyperparameters_invalid_provider(client, mock_finetune_reg
 
     assert response.status_code == 400
     assert (
-        response.json()["detail"] == "Fine tune provider 'invalid_provider' not found"
+        response.json()["message"] == "Fine tune provider 'invalid_provider' not found"
     )
 
 
@@ -660,7 +661,7 @@ def test_create_finetune_invalid_provider(client, mock_task_from_id_disk_backed)
 
     assert response.status_code == 400
     assert (
-        response.json()["detail"] == "Fine tune provider 'invalid_provider' not found"
+        response.json()["message"] == "Fine tune provider 'invalid_provider' not found"
     )
 
 
@@ -688,7 +689,7 @@ def test_create_finetune_invalid_dataset(
 
     assert response.status_code == 404
     assert (
-        response.json()["detail"]
+        response.json()["message"]
         == "Dataset split with ID 'invalid_split_id' not found"
     )
 
@@ -756,7 +757,7 @@ def test_create_finetune_no_system_message(
 
     assert response.status_code == 400
     assert (
-        response.json()["detail"]
+        response.json()["message"]
         == "System message generator or custom system message is required"
     )
 
@@ -864,7 +865,7 @@ def test_create_finetune_prompt_builder_error(
 
     assert response.status_code == 400
     assert (
-        response.json()["detail"]
+        response.json()["message"]
         == "Error generating system message using generator: test_prompt_builder. Source error: Invalid prompt configuration"
     )
 
@@ -952,7 +953,7 @@ def test_download_dataset_jsonl_invalid_format(
     )
 
     assert response.status_code == 400
-    assert response.json()["detail"] == "Dataset format 'invalid_format' not found"
+    assert response.json()["message"] == "Dataset format 'invalid_format' not found"
 
 
 def test_download_dataset_jsonl_data_strategy_invalid(
@@ -966,7 +967,7 @@ def test_download_dataset_jsonl_data_strategy_invalid(
 
     assert response.status_code == 400
     assert (
-        response.json()["detail"] == "Data strategy 'invalid_data_strategy' not found"
+        response.json()["message"] == "Data strategy 'invalid_data_strategy' not found"
     )
 
 
@@ -981,7 +982,7 @@ def test_download_dataset_jsonl_invalid_dataset(
 
     assert response.status_code == 404
     assert (
-        response.json()["detail"] == "Dataset split with ID 'invalid_split' not found"
+        response.json()["message"] == "Dataset split with ID 'invalid_split' not found"
     )
 
 
@@ -996,7 +997,8 @@ def test_download_dataset_jsonl_invalid_split(
 
     assert response.status_code == 404
     assert (
-        response.json()["detail"] == "Dataset split with name 'invalid_split' not found"
+        response.json()["message"]
+        == "Dataset split with name 'invalid_split' not found"
     )
 
 
@@ -1071,7 +1073,7 @@ def test_get_finetune_not_found(client, mock_task_from_id_disk_backed):
     response = client.get("/api/projects/project1/tasks/task1/finetunes/nonexistent")
 
     assert response.status_code == 404
-    assert response.json()["detail"] == "Finetune with ID 'nonexistent' not found"
+    assert response.json()["message"] == "Finetune with ID 'nonexistent' not found"
 
     mock_task_from_id_disk_backed.assert_called_once_with("project1", "task1")
 
diff --git a/app/desktop/studio_server/test_import_api.py b/app/desktop/studio_server/test_import_api.py
index bd6aee4c1..f40488039 100644
--- a/app/desktop/studio_server/test_import_api.py
+++ b/app/desktop/studio_server/test_import_api.py
@@ -4,6 +4,7 @@
 import pytest
 from fastapi import FastAPI
 from fastapi.testclient import TestClient
+from kiln_server.custom_errors import connect_custom_errors
 
 from app.desktop.studio_server.import_api import _show_file_dialog, connect_import_api
 
@@ -11,6 +12,7 @@
 @pytest.fixture
 def app():
     app = FastAPI()
+    connect_custom_errors(app)
     return app
 
 
@@ -36,14 +38,14 @@ def test_select_kiln_file_no_tk_root(client_no_tk):
     """Test that the endpoint raises HTTPException when tk_root is None"""
     response = client_no_tk.get("/api/select_kiln_file")
     assert response.status_code == 400
-    assert "Not running in app mode" in response.json()["detail"]
+    assert "Not running in app mode" in response.json()["message"]
 
 
 def test_select_kiln_file_with_custom_title(client_no_tk):
     """Test that custom title parameter is handled when tk_root is None"""
     response = client_no_tk.get("/api/select_kiln_file?title=Custom Title")
     assert response.status_code == 400
-    assert "Not running in app mode" in response.json()["detail"]
+    assert "Not running in app mode" in response.json()["message"]
 
 
 @patch("app.desktop.studio_server.import_api.filedialog.askopenfilename")
diff --git a/app/desktop/studio_server/test_prompt_api.py b/app/desktop/studio_server/test_prompt_api.py
index 0b1ccf678..004eff566 100644
--- a/app/desktop/studio_server/test_prompt_api.py
+++ b/app/desktop/studio_server/test_prompt_api.py
@@ -5,6 +5,7 @@
 # Create a FastAPI app and connect the prompt_api
 from fastapi import FastAPI
 from fastapi.testclient import TestClient
+from kiln_server.custom_errors import connect_custom_errors
 from kiln_ai.adapters.prompt_builders import BasePromptBuilder
 from kiln_ai.datamodel import Task
 
@@ -14,6 +15,7 @@
 @pytest.fixture
 def client():
     app = FastAPI()
+    connect_custom_errors(app)
     connect_prompt_api(app)
     return TestClient(app)
 
diff --git a/app/desktop/studio_server/test_prompt_optimization_job_api.py b/app/desktop/studio_server/test_prompt_optimization_job_api.py
index c75b35dce..79d234c22 100644
--- a/app/desktop/studio_server/test_prompt_optimization_job_api.py
+++ b/app/desktop/studio_server/test_prompt_optimization_job_api.py
@@ -36,6 +36,7 @@
 )
 from fastapi import FastAPI, HTTPException
 from fastapi.testclient import TestClient
+from kiln_server.custom_errors import connect_custom_errors
 from kiln_ai.cli.commands.package_project import PackageForTrainingConfig
 from kiln_ai.datamodel import Project, PromptOptimizationJob, Task
 from kiln_ai.datamodel.datamodel_enums import ModelProviderName, StructuredOutputMode
@@ -68,6 +69,7 @@ def _make_sdk_response(
 @pytest.fixture
 def app():
     app = FastAPI()
+    connect_custom_errors(app)
     connect_prompt_optimization_job_api(app)
     return app
 
@@ -152,7 +154,7 @@ def test_get_prompt_optimization_job_result_no_output(client, mock_api_key):
         response = client.get(f"/api/prompt_optimization_jobs/{job_id}/result")
 
         assert response.status_code == 500
-        assert "has no output" in response.json()["detail"]
+        assert "has no output" in response.json()["message"]
 
 
 def test_get_prompt_optimization_job_result_api_error(client, mock_api_key):
@@ -168,7 +170,7 @@ def test_get_prompt_optimization_job_result_api_error(client, mock_api_key):
 
         assert response.status_code == 500
         assert (
-            "Failed to get Prompt Optimization job result" in response.json()["detail"]
+            "Failed to get Prompt Optimization job result" in response.json()["message"]
         )
 
 
@@ -223,7 +225,7 @@ def test_get_prompt_optimization_job_result_no_api_key(client):
         response = client.get(f"/api/prompt_optimization_jobs/{job_id}/result")
 
         assert response.status_code == 401
-        assert "API key not configured" in response.json()["detail"]
+        assert "API key not configured" in response.json()["message"]
 
 
 def test_get_prompt_optimization_job_result_validation_error(client, mock_api_key):
@@ -1450,7 +1452,7 @@ def test_check_run_config_server_none_response(client, mock_api_key, tmp_path):
         )
 
         assert response.status_code == 500
-        assert "unknown error" in response.json()["detail"].lower()
+        assert "unknown error" in response.json()["message"].lower()
 
 
 def test_check_run_config_exception(client, mock_api_key, tmp_path):
@@ -1479,7 +1481,7 @@ def test_check_run_config_exception(client, mock_api_key, tmp_path):
         )
 
         assert response.status_code == 500
-        assert "Failed to check run config" in response.json()["detail"]
+        assert "Failed to check run config" in response.json()["message"]
 
 
 def test_check_eval_no_current_config(client, mock_api_key, tmp_path):
@@ -1748,7 +1750,7 @@ def test_check_eval_server_none_response(client, mock_api_key, tmp_path):
         )
 
         assert response.status_code == 500
-        assert "unknown error" in response.json()["detail"].lower()
+        assert "unknown error" in response.json()["message"].lower()
 
 
 def test_check_eval_exception(client, mock_api_key, tmp_path):
@@ -1777,7 +1779,7 @@ def test_check_eval_exception(client, mock_api_key, tmp_path):
         )
 
         assert response.status_code == 500
-        assert "Failed to check eval" in response.json()["detail"]
+        assert "Failed to check eval" in response.json()["message"]
 
 
 @pytest.mark.parametrize(
@@ -1865,7 +1867,7 @@ def test_start_prompt_optimization_job_no_parent_project(
         )
 
         assert response.status_code == 404
-        assert "Project not found" in response.json()["detail"]
+        assert "Project not found" in response.json()["message"]
 
 
 def test_start_prompt_optimization_job_with_tools_in_run_config(
@@ -1909,8 +1911,8 @@ def test_start_prompt_optimization_job_with_tools_in_run_config(
         )
 
         assert response.status_code == 400
-        assert "does not support" in response.json()["detail"]
-        assert "tools" in response.json()["detail"]
+        assert "does not support" in response.json()["message"]
+        assert "tools" in response.json()["message"]
 
 
 def test_start_prompt_optimization_job_server_not_authenticated(
@@ -1957,7 +1959,7 @@ def test_start_prompt_optimization_job_server_not_authenticated(
         )
 
         assert response.status_code == 500
-        assert "not authenticated" in response.json()["detail"]
+        assert "not authenticated" in response.json()["message"]
 
 
 def test_start_prompt_optimization_job_server_validation_error(
@@ -2012,7 +2014,7 @@ def test_start_prompt_optimization_job_server_validation_error(
         )
 
         assert response.status_code == 422
-        assert "Upstream validation error" in response.json()["detail"]
+        assert "Upstream validation error" in response.json()["message"]
 
 
 def test_start_prompt_optimization_job_server_none_response(
@@ -2064,7 +2066,7 @@ def test_start_prompt_optimization_job_server_none_response(
         )
 
         assert response.status_code == 500
-        assert "unknown error" in response.json()["detail"].lower()
+        assert "unknown error" in response.json()["message"].lower()
 
 
 def test_start_prompt_optimization_job_connection_error(client, mock_api_key, tmp_path):
@@ -2117,8 +2119,8 @@ class ReadError(Exception):
         )
 
         assert response.status_code == 500
-        assert "Connection error" in response.json()["detail"]
-        assert "too large" in response.json()["detail"]
+        assert "Connection error" in response.json()["message"]
+        assert "too large" in response.json()["message"]
 
 
 def test_start_prompt_optimization_job_timeout_error(client, mock_api_key, tmp_path):
@@ -2168,7 +2170,7 @@ def test_start_prompt_optimization_job_timeout_error(client, mock_api_key, tmp_p
         )
 
         assert response.status_code == 500
-        assert "Connection error" in response.json()["detail"]
+        assert "Connection error" in response.json()["message"]
 
 
 def test_start_prompt_optimization_job_general_exception(
@@ -2215,7 +2217,7 @@ def test_start_prompt_optimization_job_general_exception(
         )
 
         assert response.status_code == 500
-        assert "Failed to start Prompt Optimization job" in response.json()["detail"]
+        assert "Failed to start Prompt Optimization job" in response.json()["message"]
 
 
 def test_prompt_optimization_job_creates_run_config_on_success(
diff --git a/app/desktop/studio_server/test_provider_api.py b/app/desktop/studio_server/test_provider_api.py
index 4f67897c2..242135c25 100644
--- a/app/desktop/studio_server/test_provider_api.py
+++ b/app/desktop/studio_server/test_provider_api.py
@@ -38,6 +38,7 @@
 from fastapi import FastAPI, HTTPException
 from fastapi.responses import JSONResponse
 from fastapi.testclient import TestClient
+from kiln_server.custom_errors import connect_custom_errors
 from kiln_ai.adapters.ml_embedding_model_list import (
     EmbeddingModelName,
     KilnEmbeddingModel,
@@ -65,6 +66,7 @@
 @pytest.fixture
 def app():
     app = FastAPI()
+    connect_custom_errors(app)
     connect_provider_api(app)
     return app
 
@@ -162,7 +164,7 @@ def test_connect_api_key_kiln_copilot_empty_key(client):
     )
 
     assert response.status_code == 400
-    assert response.json() == {"detail": "API Key not found"}
+    assert response.json() == {"message": "API Key not found"}
 
 
 @patch("app.desktop.studio_server.provider_api.httpx.AsyncClient.get")
@@ -1602,7 +1604,7 @@ async def test_save_openai_compatible_providers_duplicate_name(client):
         )
 
         assert response.status_code == 400
-        assert response.json() == {"detail": "Provider with this name already exists"}
+        assert response.json() == {"message": "Provider with this name already exists"}
 
 
 @pytest.mark.asyncio
@@ -3415,6 +3417,7 @@ async def test_get_available_reranker_models(app, client):
 def test_add_user_model_success():
     """Test adding a user model successfully"""
     app = FastAPI()
+    connect_custom_errors(app)
     connect_provider_api(app)
     client = TestClient(app)
 
@@ -3447,6 +3450,7 @@ def test_add_user_model_success():
 def test_add_user_model_exact_duplicate_rejected():
     """Test that an exact duplicate (same provider_id, model_id, name, overrides) is rejected"""
     app = FastAPI()
+    connect_custom_errors(app)
     connect_provider_api(app)
     client = TestClient(app)
 
@@ -3479,12 +3483,13 @@ def test_add_user_model_exact_duplicate_rejected():
         )
 
     assert response.status_code == 400
-    assert "already exists" in response.json()["detail"]
+    assert "already exists" in response.json()["message"]
 
 
 def test_add_user_model_same_model_id_different_name_allowed():
     """Test that same model_id with different display name is allowed (not a duplicate)"""
     app = FastAPI()
+    connect_custom_errors(app)
     connect_provider_api(app)
     client = TestClient(app)
 
@@ -3524,6 +3529,7 @@ def test_add_user_model_same_model_id_different_name_allowed():
 def test_add_user_model_same_model_id_different_overrides_allowed():
     """Test that same model_id with different overrides is allowed (not a duplicate)"""
     app = FastAPI()
+    connect_custom_errors(app)
     connect_provider_api(app)
     client = TestClient(app)
 
@@ -3564,6 +3570,7 @@ def test_add_user_model_same_model_id_different_overrides_allowed():
 def test_add_user_model_same_model_id_different_provider_allowed():
     """Test that same model_id on a different provider is allowed"""
     app = FastAPI()
+    connect_custom_errors(app)
     connect_provider_api(app)
     client = TestClient(app)
 
@@ -3603,6 +3610,7 @@ def test_add_user_model_same_model_id_different_provider_allowed():
 def test_add_user_model_invalid_custom_provider():
     """Test that adding a model for a non-existent custom provider fails"""
     app = FastAPI()
+    connect_custom_errors(app)
     connect_provider_api(app)
     client = TestClient(app)
 
@@ -3624,12 +3632,13 @@ def test_add_user_model_invalid_custom_provider():
         )
 
     assert response.status_code == 400
-    assert "not found" in response.json()["detail"]
+    assert "not found" in response.json()["message"]
 
 
 def test_delete_user_model_by_id():
     """Test deleting a user model by its ID (new format)"""
     app = FastAPI()
+    connect_custom_errors(app)
     connect_provider_api(app)
     client = TestClient(app)
 
@@ -3666,6 +3675,7 @@ def test_delete_user_model_by_id():
 def test_delete_user_model_by_tuple_from_registry():
     """Test deleting a user model by provider_type/provider_id/model_id tuple (legacy format)"""
     app = FastAPI()
+    connect_custom_errors(app)
     connect_provider_api(app)
     client = TestClient(app)
 
@@ -3696,6 +3706,7 @@ def test_delete_user_model_by_tuple_from_registry():
 def test_delete_user_model_by_tuple_from_legacy_custom_models():
     """Test deleting a legacy model from custom_models by tuple (legacy format)"""
     app = FastAPI()
+    connect_custom_errors(app)
     connect_provider_api(app)
     client = TestClient(app)
 
@@ -3721,6 +3732,7 @@ def test_delete_user_model_by_tuple_from_legacy_custom_models():
 def test_delete_user_model_not_found():
     """Test deleting a non-existent model returns 404"""
     app = FastAPI()
+    connect_custom_errors(app)
     connect_provider_api(app)
     client = TestClient(app)
 
@@ -3735,12 +3747,13 @@ def test_delete_user_model_not_found():
         response = client.delete("/api/settings/user_models?id=non-existent-id")
 
     assert response.status_code == 404
-    assert "not found" in response.json()["detail"]
+    assert "not found" in response.json()["message"]
 
 
 def test_delete_user_model_bad_request_no_params():
     """Test deleting without required parameters returns 400"""
     app = FastAPI()
+    connect_custom_errors(app)
     connect_provider_api(app)
     client = TestClient(app)
 
@@ -3755,4 +3768,4 @@ def test_delete_user_model_bad_request_no_params():
         response = client.delete("/api/settings/user_models")
 
     assert response.status_code == 400
-    assert "Must specify" in response.json()["detail"]
+    assert "Must specify" in response.json()["message"]
diff --git a/app/desktop/studio_server/test_repair_api.py b/app/desktop/studio_server/test_repair_api.py
index 6b9490839..32f4ec4ce 100644
--- a/app/desktop/studio_server/test_repair_api.py
+++ b/app/desktop/studio_server/test_repair_api.py
@@ -4,6 +4,7 @@
 import pytest
 from fastapi import FastAPI
 from fastapi.testclient import TestClient
+from kiln_server.custom_errors import connect_custom_errors
 from kiln_ai.datamodel import (
     DataSource,
     DataSourceType,
@@ -24,6 +25,7 @@
 @pytest.fixture
 def app():
     app = FastAPI()
+    connect_custom_errors(app)
     connect_repair_api(app)
     return app
 
@@ -201,7 +203,7 @@ def test_repair_run_missing_model_info(
 
     # Assert
     assert response.status_code == 422
-    assert response.json()["detail"] == "Model name and provider must be specified."
+    assert response.json()["message"] == "Model name and provider must be specified."
 
 
 def test_repair_run_human_source(
diff --git a/app/desktop/studio_server/test_run_config_api.py b/app/desktop/studio_server/test_run_config_api.py
index 13a21768c..392e1d0cc 100644
--- a/app/desktop/studio_server/test_run_config_api.py
+++ b/app/desktop/studio_server/test_run_config_api.py
@@ -16,6 +16,7 @@
 )
 from fastapi import FastAPI
 from fastapi.testclient import TestClient
+from kiln_server.custom_errors import connect_custom_errors
 from kiln_ai.datamodel import Project, Task
 from kiln_ai.datamodel.basemodel import string_to_valid_name
 from kiln_ai.tools.mcp_server_tool import MCPServerTool
@@ -24,6 +25,7 @@
 @pytest.fixture
 def app():
     app = FastAPI()
+    connect_custom_errors(app)
     connect_run_config_api(app)
     return app
 
@@ -788,7 +790,7 @@ def test_tasks_compatible_with_tool_invalid_tool(client, project_and_tasks):
         )
 
     assert response.status_code == 400
-    assert response.json()["detail"] == "Tool selected is not an MCP tool."
+    assert response.json()["message"] == "Tool selected is not an MCP tool."
 
 
 def test_tasks_compatible_with_tool_empty_project(client, tmp_path):
diff --git a/app/desktop/studio_server/test_settings_api.py b/app/desktop/studio_server/test_settings_api.py
index 9e8c22c4d..ebb83453e 100644
--- a/app/desktop/studio_server/test_settings_api.py
+++ b/app/desktop/studio_server/test_settings_api.py
@@ -9,6 +9,7 @@
 from app.desktop.studio_server.settings_api import connect_settings
 from fastapi import FastAPI
 from fastapi.testclient import TestClient
+from kiln_server.custom_errors import connect_custom_errors
 from kiln_ai.utils.config import Config
 
 
@@ -21,6 +22,7 @@ def temp_home(tmp_path):
 @pytest.fixture
 def app():
     app = FastAPI()
+    connect_custom_errors(app)
     connect_settings(app)
     return app
 
@@ -186,7 +188,7 @@ def test_check_entitlements_no_api_key(self, client):
                 "/api/check_entitlements?feature_codes=prompt-optimization"
             )
             assert response.status_code == 401
-            assert "API key not configured" in response.json()["detail"]
+            assert "API key not configured" in response.json()["message"]
 
     def test_check_entitlements_single_feature_true(self, client, mock_api_key):
         mock_response = MagicMock(
@@ -278,4 +280,4 @@ def test_check_entitlements_api_error_response(self, client, mock_api_key):
                 "/api/check_entitlements?feature_codes=prompt-optimization"
             )
             assert response.status_code == 403
-            assert "Forbidden: Invalid API key" in response.json()["detail"]
+            assert "Forbidden: Invalid API key" in response.json()["message"]
diff --git a/app/desktop/studio_server/test_tool_api.py b/app/desktop/studio_server/test_tool_api.py
index f9a42ea53..720f21342 100644
--- a/app/desktop/studio_server/test_tool_api.py
+++ b/app/desktop/studio_server/test_tool_api.py
@@ -3,6 +3,13 @@
 from unittest.mock import AsyncMock, Mock, patch
 
 import pytest
+from app.desktop.studio_server.tool_api import (
+    ExternalToolApiDescription,
+    available_mcp_tools,
+    connect_tool_servers_api,
+    tool_server_from_id,
+    validate_tool_server_connectivity,
+)
 from fastapi import FastAPI, HTTPException
 from fastapi.testclient import TestClient
 from kiln_ai.datamodel.datamodel_enums import StructuredOutputMode
@@ -13,17 +20,11 @@
 from kiln_ai.datamodel.run_config import KilnAgentRunConfigProperties
 from kiln_ai.datamodel.task import Task, TaskRunConfig
 from kiln_ai.datamodel.tool_id import KILN_TASK_TOOL_ID_PREFIX
+from kiln_ai.tools.mcp_session_manager import KilnMCPError
 from kiln_ai.utils.config import MCP_SECRETS_KEY
+from kiln_server.custom_errors import connect_custom_errors
 from mcp.types import ListToolsResult, Tool
 
-from app.desktop.studio_server.tool_api import (
-    ExternalToolApiDescription,
-    available_mcp_tools,
-    connect_tool_servers_api,
-    tool_server_from_id,
-    validate_tool_server_connectivity,
-)
-
 
 @pytest.fixture
 def mock_project_from_id(test_project):
@@ -85,7 +86,7 @@ async def mock_mcp_success(tools=None):
 @asynccontextmanager
 async def mock_mcp_connection_error(error_message="Connection failed"):
     """Context manager for MCP connection errors."""
-    error = Exception(error_message)
+    error = KilnMCPError(error_message)
     patch_obj, mock_client = create_mcp_session_manager_patch(connection_error=error)
 
     with patch_obj as mock_session_manager_shared:
@@ -98,7 +99,7 @@ async def mock_mcp_connection_error(error_message="Connection failed"):
 @asynccontextmanager
 async def mock_mcp_list_tools_error(error_message="list_tools failed"):
     """Context manager for MCP list_tools errors."""
-    error = Exception(error_message)
+    error = KilnMCPError(error_message)
     patch_obj, mock_client = create_mcp_session_manager_patch(list_tools_error=error)
 
     with patch_obj as mock_session_manager_shared:
@@ -111,6 +112,7 @@ async def mock_mcp_list_tools_error(error_message="list_tools failed"):
 @pytest.fixture
 def app():
     test_app = FastAPI()
+    connect_custom_errors(test_app)
     connect_tool_servers_api(test_app)
     return test_app
 
@@ -416,7 +418,7 @@ async def test_get_tool_server_success(client, test_project):
 
 
 async def test_get_tool_server_mcp_error_handling(client, test_project):
-    """Test that MCP server errors are handled gracefully and return empty tools"""
+    """Test that MCP server errors are surfaced with HTTP 503 and the error message"""
     # First create a tool server
     tool_data = {
         "name": "failing_mcp_tool",
@@ -443,12 +445,13 @@ async def test_get_tool_server_mcp_error_handling(client, test_project):
 
         # Mock retrieval with list_tools error
         async with mock_mcp_list_tools_error("Connection failed"):
-            # The API should handle the exception gracefully
-            # For now, let's test that it raises the exception since that's the current behavior
-            with pytest.raises(Exception, match="Connection failed"):
-                client.get(
-                    f"/api/projects/{test_project.id}/tool_servers/{tool_server_id}"
-                )
+            # The API should surface the error as HTTP 503 with the error message in detail
+            response = client.get(
+                f"/api/projects/{test_project.id}/tool_servers/{tool_server_id}"
+            )
+            assert response.status_code == 503
+            result = response.json()
+            assert "Connection failed" in result["message"]
 
 
 def test_get_tool_server_not_found(client, test_project):
@@ -464,7 +467,61 @@ def test_get_tool_server_not_found(client, test_project):
 
         assert response.status_code == 404
         result = response.json()
-        assert result["detail"] == "Tool server not found"
+        assert result["message"] == "Tool server not found"
+
+
+async def test_get_tool_server_config_returns_file_data_without_connecting(
+    client, test_project
+):
+    """The /config endpoint must return tool server data without attempting
+    a connection, so the edit form loads even when the MCP server is unreachable."""
+    tool_data = {
+        "name": "config_test_tool",
+        "server_url": "https://example.com/api",
+        "headers": {},
+        "description": "Tool for config test",
+        "is_archived": False,
+    }
+
+    with patch(
+        "app.desktop.studio_server.tool_api.project_from_id"
+    ) as mock_project_from_id:
+        mock_project_from_id.return_value = test_project
+
+        async with mock_mcp_success():
+            create_response = client.post(
+                f"/api/projects/{test_project.id}/connect_remote_mcp",
+                json=tool_data,
+            )
+            assert create_response.status_code == 200
+        tool_server_id = create_response.json()["id"]
+
+        # Call /config while the MCP connection is broken — must still succeed
+        async with mock_mcp_list_tools_error("Connection failed"):
+            response = client.get(
+                f"/api/projects/{test_project.id}/tool_servers/{tool_server_id}/config"
+            )
+
+        assert response.status_code == 200
+        result = response.json()
+        assert result["name"] == "config_test_tool"
+        assert result["type"] == "remote_mcp"
+        assert result["available_tools"] == []
+        assert result["missing_secrets"] == []
+
+
+def test_get_tool_server_config_not_found(client, test_project):
+    with patch(
+        "app.desktop.studio_server.tool_api.project_from_id"
+    ) as mock_project_from_id:
+        mock_project_from_id.return_value = test_project
+
+        response = client.get(
+            f"/api/projects/{test_project.id}/tool_servers/nonexistent-id/config"
+        )
+
+        assert response.status_code == 404
+        assert response.json()["message"] == "Tool server not found"
 
 
 def test_get_available_tools_empty(client, test_project):
@@ -1620,7 +1677,7 @@ def test_delete_tool_server_not_found(client, test_project):
             f"/api/projects/{test_project.id}/tool_servers/non-existent-id"
         )
         assert response.status_code == 404
-        assert "Tool server not found" in response.json()["detail"]
+        assert "Tool server not found" in response.json()["message"]
 
 
 def test_delete_tool_server_project_not_found(client):
@@ -1630,7 +1687,7 @@ def test_delete_tool_server_project_not_found(client):
         "/api/projects/non-existent-project/tool_servers/some-tool-id"
     )
     assert response.status_code == 404
-    assert "Project not found" in response.json()["detail"]
+    assert "Project not found" in response.json()["message"]
 
 
 async def test_delete_tool_server_affects_available_servers_list(client, test_project):
@@ -3035,7 +3092,7 @@ async def test_edit_local_mcp_404(client, test_project, edit_local_server_data):
             json=edit_local_server_data,
         )
         assert response.status_code == 404
-        assert response.json() == {"detail": "Tool server not found"}
+        assert response.json() == {"message": "Tool server not found"}
 
 
 @pytest.fixture
@@ -3085,7 +3142,7 @@ async def test_edit_local_mcp_wrong_type(
         )
         assert response.status_code == 400
         assert response.json() == {
-            "detail": "Existing tool server is not a local MCP server. You can't edit a non-local MCP server with this endpoint."
+            "message": "Existing tool server is not a local MCP server. You can't edit a non-local MCP server with this endpoint."
         }
 
 
@@ -3165,7 +3222,7 @@ async def test_edit_remote_mcp_404(client, test_project, edit_remote_server_data
             json=edit_remote_server_data,
         )
         assert response.status_code == 404
-        assert response.json() == {"detail": "Tool server not found"}
+        assert response.json() == {"message": "Tool server not found"}
 
 
 async def test_edit_remote_mcp_wrong_type(
@@ -3183,7 +3240,7 @@ async def test_edit_remote_mcp_wrong_type(
         )
         assert response.status_code == 400
         assert response.json() == {
-            "detail": "Existing tool server is not a remote MCP server. You can't edit a non-remote MCP server with this endpoint."
+            "message": "Existing tool server is not a remote MCP server. You can't edit a non-remote MCP server with this endpoint."
         }
 
 
@@ -4108,7 +4165,7 @@ async def test_add_kiln_task_tool_validation_task_not_found(client, test_project
         )
 
         assert response.status_code == 404
-        assert "Task not found" in response.json()["detail"]
+        assert "Task not found" in response.json()["message"]
 
 
 @pytest.mark.asyncio
@@ -4157,7 +4214,7 @@ async def test_add_kiln_task_tool_validation_run_config_not_found(client, test_p
 
         assert response.status_code == 400
         assert (
-            "Run config not found for the specified task" in response.json()["detail"]
+            "Run config not found for the specified task" in response.json()["message"]
         )
 
 
@@ -4278,7 +4335,7 @@ async def test_edit_kiln_task_tool_validation_task_not_found(client, test_projec
         )
 
         assert response.status_code == 404
-        assert "Task not found" in response.json()["detail"]
+        assert "Task not found" in response.json()["message"]
 
 
 @pytest.mark.asyncio
@@ -4346,7 +4403,7 @@ async def test_edit_kiln_task_tool_validation_run_config_not_found(
 
         assert response.status_code == 400
         assert (
-            "Run config not found for the specified task" in response.json()["detail"]
+            "Run config not found for the specified task" in response.json()["message"]
         )
 
 
@@ -4463,8 +4520,8 @@ async def test_get_tool_definition_tool_not_found(client, test_project):
 
         assert response.status_code == 404
         result = response.json()
-        assert "Tool not found or could not be instantiated" in result["detail"]
-        assert invalid_tool_id in result["detail"]
+        assert "Tool not found or could not be instantiated" in result["message"]
+        assert invalid_tool_id in result["message"]
 
 
 @pytest.mark.asyncio
@@ -4484,4 +4541,4 @@ async def test_get_tool_definition_task_not_found(client, test_project):
         )
 
         assert response.status_code == 404
-        assert "Task not found" in response.json()["detail"]
+        assert "Task not found" in response.json()["message"]
diff --git a/app/desktop/studio_server/tool_api.py b/app/desktop/studio_server/tool_api.py
index 549a4759d..5874fb9e0 100644
--- a/app/desktop/studio_server/tool_api.py
+++ b/app/desktop/studio_server/tool_api.py
@@ -1,3 +1,4 @@
+import logging
 from datetime import datetime
 from enum import Enum
 from typing import Any, Dict, List
@@ -10,6 +11,7 @@
     LocalServerProperties,
     RemoteServerProperties,
     ToolServerType,
+    tool_server_type_to_string,
 )
 from kiln_ai.datamodel.tool_id import (
     MCP_LOCAL_TOOL_ID_PREFIX,
@@ -20,7 +22,10 @@
     build_rag_tool_id,
 )
 from kiln_ai.tools.kiln_task_tool import KilnTaskTool
-from kiln_ai.tools.mcp_session_manager import MCPSessionManager
+from kiln_ai.tools.mcp_session_manager import (
+    KilnMCPError,
+    MCPSessionManager,
+)
 from kiln_ai.tools.tool_registry import tool_from_id
 from kiln_ai.utils.config import Config
 from kiln_ai.utils.exhaustive_error import raise_exhaustive_enum_error
@@ -29,6 +34,8 @@
 from mcp.types import Tool as MCPTool
 from pydantic import BaseModel, Field
 
+logger = logging.getLogger(__name__)
+
 
 class KilnToolServerDescription(BaseModel):
     """
@@ -428,15 +435,53 @@ async def get_tool_server(
         available_tools = []
         match tool_server.type:
             case ToolServerType.remote_mcp | ToolServerType.local_mcp:
-                async with MCPSessionManager.shared().mcp_client(
-                    tool_server
-                ) as session:
-                    tools_result = await session.list_tools()
-
-                    available_tools = [
-                        ExternalToolApiDescription.tool_from_mcp_tool(tool)
-                        for tool in tools_result.tools
+                try:
+                    async with MCPSessionManager.shared().mcp_client(
+                        tool_server
+                    ) as session:
+                        tools_result = await session.list_tools()
+
+                        available_tools = [
+                            ExternalToolApiDescription.tool_from_mcp_tool(tool)
+                            for tool in tools_result.tools
+                        ]
+                except (KilnMCPError, ValueError) as e:
+                    context_lines = [
+                        "MCP call failed: list_tools",
+                        f"Tool server: {tool_server.name} ({tool_server.id})",
+                        f"Type: {tool_server_type_to_string(tool_server.type)}",
                     ]
+                    props = tool_server.properties or {}
+                    if tool_server.type == ToolServerType.local_mcp:
+                        command = props.get("command")
+                        args = props.get("args")
+                        command_text = (
+                            command if isinstance(command, str) else "<unknown>"
+                        )
+                        args_text = (
+                            " ".join(args)
+                            if isinstance(args, list)
+                            and all(isinstance(arg, str) for arg in args)
+                            else "<unknown>"
+                        )
+                        context_lines.append(f"Command: {command_text} {args_text}")
+                    elif tool_server.type == ToolServerType.remote_mcp:
+                        server_url = props.get("server_url")
+                        server_url_text = (
+                            server_url if isinstance(server_url, str) else "<unknown>"
+                        )
+                        context_lines.append(f"Server URL: {server_url_text}")
+
+                    detail = "\n".join(context_lines) + f"\n\nError: {e}"
+                    stderr_text = e.stderr if isinstance(e, KilnMCPError) else ""
+                    if stderr_text:
+                        # Truncate the error to 4kb
+                        if len(stderr_text) > 4096:
+                            stderr_text = stderr_text[:4096] + "\n... (truncated)"
+                        detail += f"\n\nMCP server stderr:\n{stderr_text}"
+
+                    logger.error("MCP list_tools failed:\n%s", e, exc_info=True)
+                    raise HTTPException(status_code=503, detail=detail) from e
             case ToolServerType.kiln_task:
                 available_tools = [
                     await ExternalToolApiDescription.tool_from_kiln_task_tool(
@@ -460,6 +505,23 @@ async def get_tool_server(
             missing_secrets=[],
         )
 
+    @app.get("/api/projects/{project_id}/tool_servers/{tool_server_id}/config")
+    async def get_tool_server_config(
+        project_id: str, tool_server_id: str
+    ) -> ExternalToolServerApiDescription:
+        tool_server = tool_server_from_id(project_id, tool_server_id)
+        return ExternalToolServerApiDescription(
+            id=tool_server.id,
+            name=tool_server.name,
+            type=tool_server.type,
+            description=tool_server.description,
+            created_at=tool_server.created_at,
+            created_by=tool_server.created_by,
+            properties=tool_server.properties,
+            available_tools=[],
+            missing_secrets=[],
+        )
+
     @app.post("/api/projects/{project_id}/connect_remote_mcp")
     async def connect_remote_mcp(
         project_id: str, tool_data: ExternalToolServerCreationRequest
diff --git a/app/web_ui/src/lib/api_schema.d.ts b/app/web_ui/src/lib/api_schema.d.ts
index d7bb96796..754759f8a 100644
--- a/app/web_ui/src/lib/api_schema.d.ts
+++ b/app/web_ui/src/lib/api_schema.d.ts
@@ -2150,6 +2150,23 @@ export interface paths {
         patch?: never;
         trace?: never;
     };
+    "/api/projects/{project_id}/tool_servers/{tool_server_id}/config": {
+        parameters: {
+            query?: never;
+            header?: never;
+            path?: never;
+            cookie?: never;
+        };
+        /** Get Tool Server Config */
+        get: operations["get_tool_server_config_api_projects__project_id__tool_servers__tool_server_id__config_get"];
+        put?: never;
+        post?: never;
+        delete?: never;
+        options?: never;
+        head?: never;
+        patch?: never;
+        trace?: never;
+    };
     "/api/projects/{project_id}/connect_remote_mcp": {
         parameters: {
             query?: never;
@@ -6232,11 +6249,6 @@ export interface components {
             } | unknown[] | null;
             /** Tags */
             tags?: string[] | null;
-            /**
-             * Task Run Id
-             * @description When set, continue an existing session. The new message is appended to the run's trace.
-             */
-            task_run_id?: string | null;
         };
         /**
          * SampleApi
@@ -12075,6 +12087,38 @@ export interface operations {
             };
         };
     };
+    get_tool_server_config_api_projects__project_id__tool_servers__tool_server_id__config_get: {
+        parameters: {
+            query?: never;
+            header?: never;
+            path: {
+                project_id: string;
+                tool_server_id: string;
+            };
+            cookie?: never;
+        };
+        requestBody?: never;
+        responses: {
+            /** @description Successful Response */
+            200: {
+                headers: {
+                    [name: string]: unknown;
+                };
+                content: {
+                    "application/json": components["schemas"]["ExternalToolServerApiDescription"];
+                };
+            };
+            /** @description Validation Error */
+            422: {
+                headers: {
+                    [name: string]: unknown;
+                };
+                content: {
+                    "application/json": components["schemas"]["HTTPValidationError"];
+                };
+            };
+        };
+    };
     connect_remote_mcp_api_projects__project_id__connect_remote_mcp_post: {
         parameters: {
             query?: never;
diff --git a/app/web_ui/src/lib/ui/error_details_block.svelte b/app/web_ui/src/lib/ui/error_details_block.svelte
new file mode 100644
index 000000000..ec870ee78
--- /dev/null
+++ b/app/web_ui/src/lib/ui/error_details_block.svelte
@@ -0,0 +1,51 @@
+<script lang="ts">
+  import Output from "./output.svelte"
+  import MarkdownBlock from "./markdown_block.svelte"
+  import { view_logs } from "$lib/utils/logs"
+
+  export let title: string
+  export let error_messages: string[]
+  export let troubleshooting_steps: string[] = []
+  export let markdown: boolean = false
+  export let trusted: boolean = false
+  export let show_logs: boolean = true
+</script>
+
+<div
+  class="mb-6 flex flex-col gap-4 max-w-[600px] mx-auto border p-4 rounded-md"
+>
+  <span class="font-bold text-error">{title}</span>
+
+  {#if troubleshooting_steps.length > 0}
+    <div class="flex flex-col gap-2">
+      <span class="font-medium">Troubleshooting Steps</span>
+      <ol class="text-sm list-decimal list-outside pl-6 flex flex-col gap-2">
+        {#each troubleshooting_steps as step}
+          <li>
+            {#if markdown && trusted}
+              <MarkdownBlock markdown_text={step} />
+            {:else}
+              {step}
+            {/if}
+          </li>
+        {/each}
+      </ol>
+    </div>
+  {/if}
+
+  {#if show_logs}
+    <div class="flex flex-col gap-2">
+      <span class="font-medium">Error Details</span>
+      <Output
+        raw_output={error_messages.join("\n\n")}
+        hide_toggle={false}
+        max_height="120px"
+      />
+    </div>
+    <div>
+      <button type="button" class="link" on:click={view_logs}>
+        View Logs
+      </button>
+    </div>
+  {/if}
+</div>
diff --git a/app/web_ui/src/lib/utils/update.ts b/app/web_ui/src/lib/utils/update.ts
index 42eaca30a..2e746f0cf 100644
--- a/app/web_ui/src/lib/utils/update.ts
+++ b/app/web_ui/src/lib/utils/update.ts
@@ -1,7 +1,7 @@
 import { createKilnError, KilnError } from "$lib/utils/error_handlers"
 import { writable } from "svelte/store"
 
-export const app_version = "0.24.0"
+export const app_version = "0.25.0"
 
 export type UpdateCheckResult = {
   has_update: boolean
diff --git a/app/web_ui/src/routes/(app)/optimize/[project_id]/[task_id]/+page.svelte b/app/web_ui/src/routes/(app)/optimize/[project_id]/[task_id]/+page.svelte
index ce26bfdd6..fdcaea657 100644
--- a/app/web_ui/src/routes/(app)/optimize/[project_id]/[task_id]/+page.svelte
+++ b/app/web_ui/src/routes/(app)/optimize/[project_id]/[task_id]/+page.svelte
@@ -494,7 +494,7 @@
                   </td>
                   <td>
                     {#if isKilnAgentRunConfig(config.run_config_properties)}
-                      <span class="text-gray-500">Standard</span>
+                      <span class="text-gray-500">Agent</span>
                     {:else}
                       <span class="text-gray-500">MCP</span>
                     {/if}
diff --git a/app/web_ui/src/routes/(app)/prompts/[project_id]/[task_id]/+page.svelte b/app/web_ui/src/routes/(app)/prompts/[project_id]/[task_id]/+page.svelte
index dc4e1b491..ef04f134b 100644
--- a/app/web_ui/src/routes/(app)/prompts/[project_id]/[task_id]/+page.svelte
+++ b/app/web_ui/src/routes/(app)/prompts/[project_id]/[task_id]/+page.svelte
@@ -14,6 +14,7 @@
   import type { Task } from "$lib/types"
   import { createKilnError, KilnError } from "$lib/utils/error_handlers"
   import { getPromptType } from "./prompt_generators/prompt_generators"
+  import InfoTooltip from "$lib/ui/info_tooltip.svelte"
   import Banner from "$lib/ui/banner.svelte"
   import Float from "$lib/ui/float.svelte"
 
@@ -92,11 +93,19 @@
     label: string
     sortable: boolean
     sortKey?: SortableColumn
+    tooltip?: string
   }
 
   const tableColumns: TableColumn[] = [
     { key: "name", label: "Name", sortable: true, sortKey: "name" },
-    { key: "type", label: "Type", sortable: true, sortKey: "type" },
+    {
+      key: "type",
+      label: "Type",
+      sortable: true,
+      sortKey: "type",
+      tooltip:
+        "How the prompt was created. 'Frozen' means it's a fixed snapshot of the task prompt from a saved run configuration.",
+    },
     { key: "prompt_preview", label: "Prompt Preview", sortable: false },
     {
       key: "created_at",
@@ -213,6 +222,14 @@
                           class="hover:bg-base-200 cursor-pointer"
                         >
                           {column.label}
+                          {#if column.tooltip}
+                            <span class="font-normal">
+                              <InfoTooltip
+                                tooltip_text={column.tooltip}
+                                no_pad
+                              />
+                            </span>
+                          {/if}
                           <span class="inline-block w-3 text-center">
                             {sortColumn === sortKey
                               ? sortDirection === "asc"
@@ -222,7 +239,17 @@
                           </span>
                         </th>
                       {:else}
-                        <th>{column.label}</th>
+                        <th>
+                          {column.label}
+                          {#if column.tooltip}
+                            <span class="font-normal">
+                              <InfoTooltip
+                                tooltip_text={column.tooltip}
+                                no_pad
+                              />
+                            </span>
+                          {/if}
+                        </th>
                       {/if}
                     {/each}
                     <th style="width: 3%;"></th>
diff --git a/app/web_ui/src/routes/(app)/settings/manage_tools/[project_id]/add_tools/local_mcp/edit_local_tool.svelte b/app/web_ui/src/routes/(app)/settings/manage_tools/[project_id]/add_tools/local_mcp/edit_local_tool.svelte
index aee0dae0f..242a55ab5 100644
--- a/app/web_ui/src/routes/(app)/settings/manage_tools/[project_id]/add_tools/local_mcp/edit_local_tool.svelte
+++ b/app/web_ui/src/routes/(app)/settings/manage_tools/[project_id]/add_tools/local_mcp/edit_local_tool.svelte
@@ -12,8 +12,7 @@
   import { uncache_available_tools } from "$lib/stores"
   import type { ExternalToolServerApiDescription } from "$lib/types"
   import posthog from "posthog-js"
-  import { view_logs } from "$lib/utils/logs"
-  import Output from "$lib/ui/output.svelte"
+  import ErrorDetailsBlock from "$lib/ui/error_details_block.svelte"
 
   $: project_id = $page.params.project_id!
 
@@ -374,53 +373,16 @@
       </FormList>
 
       {#if error}
-        <div
-          class="mb-6 flex flex-col gap-4 max-w-[600px] mx-auto border p-4 rounded-md"
-        >
-          <span class="font-bold text-error"
-            >Could Not Connect to MCP Server</span
-          >
-
-          <div class="flex flex-col gap-2">
-            <span class="font-medium">Troubleshooting Steps</span>
-            <ol
-              class="text-sm list-decimal list-outside pl-6 flex flex-col gap-2"
-            >
-              <li>
-                Check the Error Details below for information about the issue.
-              </li>
-              <li>
-                Check the server's documentation for the correct setup
-                (dependencies, etc.).
-              </li>
-              <li>
-                Ensure your command <span
-                  class="font-mono text-xs font-bold bg-base-200 p-1 rounded-sm"
-                  >{command}
-                  {args}</span
-                > runs in your terminal. If you had to install libraries or dependencies,
-                restart the Kiln app before trying again.
-              </li>
-              <li>
-                Check Kiln logs for additional details. <button
-                  type="button"
-                  class="link"
-                  on:click={view_logs}
-                >
-                  View Logs
-                </button>
-              </li>
-            </ol>
-          </div>
-          <div class="flex flex-col gap-2">
-            <span class="font-medium">Error Details</span>
-            <Output
-              raw_output={error.getErrorMessages().join("\n\n")}
-              hide_toggle={false}
-              max_height="120px"
-            />
-          </div>
-        </div>
+        <ErrorDetailsBlock
+          title="Could Not Connect to MCP Server"
+          error_messages={error.getErrorMessages()}
+          troubleshooting_steps={[
+            "Check the Error Details below for information about the issue.",
+            "Check the server's documentation for the correct setup (dependencies, etc.).",
+            `Ensure your command ${command} ${args} runs in your terminal. If you had to install libraries or dependencies, restart the Kiln app before trying again.`,
+            "Check Kiln logs for additional details.",
+          ]}
+        />
       {/if}
     </FormContainer>
   </div>
diff --git a/app/web_ui/src/routes/(app)/settings/manage_tools/[project_id]/add_tools/remote_mcp/edit_remote_tool.svelte b/app/web_ui/src/routes/(app)/settings/manage_tools/[project_id]/add_tools/remote_mcp/edit_remote_tool.svelte
index 0373cbf90..182e745a1 100644
--- a/app/web_ui/src/routes/(app)/settings/manage_tools/[project_id]/add_tools/remote_mcp/edit_remote_tool.svelte
+++ b/app/web_ui/src/routes/(app)/settings/manage_tools/[project_id]/add_tools/remote_mcp/edit_remote_tool.svelte
@@ -12,6 +12,7 @@
   import type { ExternalToolServerApiDescription } from "$lib/types"
   import Warning from "$lib/ui/warning.svelte"
   import posthog from "posthog-js"
+  import ErrorDetailsBlock from "$lib/ui/error_details_block.svelte"
 
   $: project_id = $page.params.project_id!
 
@@ -230,7 +231,6 @@
     <FormContainer
       submit_label="Connect"
       on:submit={connect_remote_mcp}
-      bind:error
       bind:submitting
     >
       <FormElement
@@ -317,6 +317,19 @@
           </div>
         </div>
       </FormList>
+
+      {#if error}
+        <ErrorDetailsBlock
+          title="Could Not Connect to MCP Server"
+          error_messages={error.getErrorMessages()}
+          troubleshooting_steps={[
+            "Verify the URL is correct.",
+            "Verify the server is running and accessible.",
+            "Check your network connection.",
+            "Check Kiln logs for additional details.",
+          ]}
+        />
+      {/if}
     </FormContainer>
   </div>
 </div>
diff --git a/app/web_ui/src/routes/(app)/settings/manage_tools/[project_id]/edit_tool_server/[tool_server_id]/+page.svelte b/app/web_ui/src/routes/(app)/settings/manage_tools/[project_id]/edit_tool_server/[tool_server_id]/+page.svelte
index 67802aaca..0d087b352 100644
--- a/app/web_ui/src/routes/(app)/settings/manage_tools/[project_id]/edit_tool_server/[tool_server_id]/+page.svelte
+++ b/app/web_ui/src/routes/(app)/settings/manage_tools/[project_id]/edit_tool_server/[tool_server_id]/+page.svelte
@@ -34,7 +34,7 @@
 
       // Fetch the specific tool by ID
       const { data, error: fetch_error } = await client.GET(
-        "/api/projects/{project_id}/tool_servers/{tool_server_id}",
+        "/api/projects/{project_id}/tool_servers/{tool_server_id}/config",
         {
           params: {
             path: {
diff --git a/app/web_ui/src/routes/(app)/settings/manage_tools/[project_id]/tool_servers/[tool_server_id]/+page.svelte b/app/web_ui/src/routes/(app)/settings/manage_tools/[project_id]/tool_servers/[tool_server_id]/+page.svelte
index 731d25e63..232ca18e8 100644
--- a/app/web_ui/src/routes/(app)/settings/manage_tools/[project_id]/tool_servers/[tool_server_id]/+page.svelte
+++ b/app/web_ui/src/routes/(app)/settings/manage_tools/[project_id]/tool_servers/[tool_server_id]/+page.svelte
@@ -19,6 +19,7 @@
   import { selected_tool_for_task } from "$lib/stores/tools_store"
   import TableButton from "../../../../../generate/[project_id]/[task_id]/table_button.svelte"
   import Float from "$lib/ui/float.svelte"
+  import ErrorDetailsBlock from "$lib/ui/error_details_block.svelte"
 
   $: project_id = $page.params.project_id!
   $: tool_server_id = $page.params.tool_server_id!
@@ -409,7 +410,7 @@
     action_buttons={[
       {
         label: "Edit",
-        href: `/settings/manage_tools/${project_id}/edit_tool_server/${tool_server?.id}`,
+        href: `/settings/manage_tools/${project_id}/edit_tool_server/${tool_server_id}`,
       },
       {
         label: is_archived ? "Unarchive" : "Archive",
@@ -489,17 +490,17 @@
         <div class="loading loading-spinner loading-lg"></div>
       </div>
     {:else if loading_error}
-      <div
-        class="w-full min-h-[50vh] flex flex-col justify-center items-center gap-2"
-      >
-        <div class="font-medium">Error Loading Tool</div>
-        <div class="text-error text-sm">
-          {loading_error.getMessage() || "An unknown error occurred"}
-        </div>
-        <button class="btn btn-primary mt-4" on:click={goBack}>
-          Back to Tools
-        </button>
-      </div>
+      <ErrorDetailsBlock
+        title="Error Loading Tool Server"
+        error_messages={loading_error.getErrorMessages()}
+        troubleshooting_steps={[
+          "Review the configuration using the **Edit** button at the top of this page.",
+          "If the server is unavailable, try again later.",
+          "Check Kiln logs for more details.",
+        ]}
+        markdown={true}
+        trusted={true}
+      />
     {:else if tool_server}
       <!-- Row 1: Properties and Connection Details side by side -->
       <div class="flex flex-col lg:flex-row gap-8 lg:gap-16 mb-10">
diff --git a/app/web_ui/src/routes/(app)/specs/[project_id]/[task_id]/select_template/+page.svelte b/app/web_ui/src/routes/(app)/specs/[project_id]/[task_id]/select_template/+page.svelte
index 70d32303b..235e1df4c 100644
--- a/app/web_ui/src/routes/(app)/specs/[project_id]/[task_id]/select_template/+page.svelte
+++ b/app/web_ui/src/routes/(app)/specs/[project_id]/[task_id]/select_template/+page.svelte
@@ -41,6 +41,7 @@
         task_id,
       )
       current_params.set("tool_function_name", tool_function_name)
+      current_params.set("tool_id", selected_tool)
     }
     goto(
       `/specs/${project_id}/${task_id}/spec_builder?${current_params.toString()}`,
diff --git a/app/web_ui/src/routes/(app)/specs/[project_id]/[task_id]/spec_builder/+page.svelte b/app/web_ui/src/routes/(app)/specs/[project_id]/[task_id]/spec_builder/+page.svelte
index b7faed935..1506bdbab 100644
--- a/app/web_ui/src/routes/(app)/specs/[project_id]/[task_id]/spec_builder/+page.svelte
+++ b/app/web_ui/src/routes/(app)/specs/[project_id]/[task_id]/spec_builder/+page.svelte
@@ -78,6 +78,9 @@
   let initial_property_values: Record<string, string | null> = {}
   let evaluate_full_trace = false
 
+  // Tool use spec: tool_id is not a form field but is required in the saved properties
+  let selected_tool_id: string | null = null
+
   // Copilot availability
   let has_kiln_copilot = false
   let default_run_config_has_tools = false
@@ -237,13 +240,14 @@
       property_values = values
       initial_property_values = { ...values }
 
-      // Override tool_function_name if provided in URL
+      // Override tool fields if provided in URL
       const tool_function_name_param =
         $page.url.searchParams.get("tool_function_name")
       if (tool_function_name_param) {
         property_values["tool_function_name"] = tool_function_name_param
         initial_property_values["tool_function_name"] = tool_function_name_param
       }
+      selected_tool_id = $page.url.searchParams.get("tool_id")
     } catch (e) {
       loading_error = createKilnError(e)
     } finally {
@@ -379,6 +383,7 @@
     const properties = {
       spec_type: spec_type,
       ...filteredValues,
+      ...(selected_tool_id ? { tool_id: selected_tool_id } : {}),
     } as SpecProperties
 
     // Call the appropriate endpoint based on whether copilot is being used
diff --git a/checks.sh b/checks.sh
index bb53d64cf..f753b19e2 100755
--- a/checks.sh
+++ b/checks.sh
@@ -31,14 +31,14 @@ echo $PWD
 headerStart="\n\033[4;34m=== "
 headerEnd=" ===\033[0m\n"
 
-echo "${headerStart}Checking Python: uvx ruff check ${headerEnd}"
-uvx ruff check
+echo "${headerStart}Checking Python: uv run ruff check ${headerEnd}"
+uv run ruff check
 
-echo "${headerStart}Checking Python: uvx ruff format --check ${headerEnd}"
-uvx ruff format --check .
+echo "${headerStart}Checking Python: uv run ruff format --check ${headerEnd}"
+uv run ruff format --check .
 
-echo "${headerStart}Checking Python Types: uvx ty check${headerEnd}"
-uvx ty check
+echo "${headerStart}Checking Python Types: uv run ty check${headerEnd}"
+uv run ty check
 
 echo "${headerStart}Checking for Misspellings${headerEnd}"
 if command -v misspell >/dev/null 2>&1; then
diff --git a/hooks_mcp.yaml b/hooks_mcp.yaml
index ff383c2dc..8374e6997 100644
--- a/hooks_mcp.yaml
+++ b/hooks_mcp.yaml
@@ -12,23 +12,23 @@ actions:
 
   - name: "lint_python"
     description: "Lint the python source code, checking for errors and warnings"
-    command: "uvx ruff check"
+    command: "uv run ruff check"
 
   - name: "lint_fix_python"
     description: "Lint the pythong source code, fixing errors and warnings which it can fix. Not all errors can be fixed automatically."
-    command: "uvx ruff check --fix"
+    command: "uv run ruff check --fix"
 
   - name: "check_format_python"
     description: "Check if the python source code is formatted correctly"
-    command: "uvx ruff format --check ."
+    command: "uv run ruff format --check ."
 
   - name: "format_python"
     description: "Format the python source code"
-    command: "uvx ruff format ."
+    command: "uv run ruff format ."
 
   - name: "typecheck_python"
     description: "Typecheck the source code"
-    command: "uvx ty check"
+    command: "uv run ty check"
 
   - name: "test_file_python"
     description: "Run tests in a specific python file or directory"
diff --git a/libs/core/README.md b/libs/core/README.md
index 76930c83b..a4ea0b7eb 100644
--- a/libs/core/README.md
+++ b/libs/core/README.md
@@ -48,6 +48,7 @@ The library has a [comprehensive set of docs](https://kiln-ai.github.io/Kiln/kil
   - [Load a LlamaIndex Vector Store](#load-a-llamaindex-vector-store)
   - [Example: LanceDB Cloud](#example-lancedb-cloud)
   - [Deploy RAG without LlamaIndex](#deploy-rag-without-llamaindex)
+- [Connecting to Telemetry / MLOps](#connecting-to-telemetry--mlops-opentelemetry-braintrust-etc)
 - [Full API Reference](#full-api-reference)
 
 ## Installation
@@ -432,6 +433,18 @@ After export, query your data using [LlamaIndex](https://developers.llamaindex.a
 
 While Kiln is designed for deploying to LlamaIndex, you don't need to use it. The `iter_llama_index_nodes` returns a `TextNode` object which includes all the data you need to build a RAG index in any stack: embedding, text, document name, chunk ID, etc.
 
+## Connecting to Telemetry / MLOps (OpenTelemetry, Braintrust, etc)
+
+You can connect the Kiln SDK to a wide range of MLOps, trace tracking, and telemetry platforms.
+
+Kiln uses the LiteLLM SDK, which supports all major telemetry providers. See LiteLLM's documentation for how to set up each provider:
+
+- [OpenTelemetry](https://docs.litellm.ai/docs/observability/opentelemetry_integration)
+- [Braintrust](https://docs.litellm.ai/docs/observability/braintrust)
+- [MLFlow](https://docs.litellm.ai/docs/observability/mlflow)
+- [LangFuse](https://docs.litellm.ai/docs/observability/langfuse_otel_integration)
+- Many more (see LiteLLM documentation)
+
 ## Full API Reference
 
 The library can do a lot more than the examples we've shown here.
diff --git a/libs/core/kiln_ai/adapters/chat/test_chat_formatter.py b/libs/core/kiln_ai/adapters/chat/test_chat_formatter.py
index e0138a954..2903b6eee 100644
--- a/libs/core/kiln_ai/adapters/chat/test_chat_formatter.py
+++ b/libs/core/kiln_ai/adapters/chat/test_chat_formatter.py
@@ -146,6 +146,50 @@ def test_multiturn_formatter_next_turn():
     assert formatter.next_turn("assistant response") is None
 
 
+def test_multiturn_formatter_preserves_tool_call_messages():
+    prior_trace = [
+        {"role": "system", "content": "You are a helpful assistant."},
+        {"role": "user", "content": "4"},
+        {
+            "role": "assistant",
+            "content": "",
+            "reasoning_content": "Let me multiply 4 by 7.\n",
+            "tool_calls": [
+                {
+                    "id": "call_abc123",
+                    "function": {"arguments": '{"a": 4, "b": 7}', "name": "multiply"},
+                    "type": "function",
+                }
+            ],
+        },
+        {
+            "content": "28",
+            "role": "tool",
+            "tool_call_id": "call_abc123",
+            "kiln_task_tool_data": None,
+        },
+        {
+            "role": "assistant",
+            "content": "4 multiplied by 7 is 28.",
+            "reasoning_content": "Done.\n",
+        },
+    ]
+    formatter = MultiturnFormatter(prior_trace=prior_trace, user_input="now double it")
+    initial = formatter.initial_messages()
+    assert initial == prior_trace
+    assert initial[2]["tool_calls"][0]["id"] == "call_abc123"
+    assert initial[2]["tool_calls"][0]["function"]["name"] == "multiply"
+    assert initial[3]["role"] == "tool"
+    assert initial[3]["tool_call_id"] == "call_abc123"
+
+    first = formatter.next_turn()
+    assert first is not None
+    assert len(first.messages) == 1
+    assert first.messages[0].role == "user"
+    assert first.messages[0].content == "now double it"
+    assert first.final_call
+
+
 def test_format_user_message():
     # String
     assert format_user_message("test input") == "test input"
diff --git a/libs/core/kiln_ai/adapters/litellm_utils/__init__.py b/libs/core/kiln_ai/adapters/litellm_utils/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/libs/core/kiln_ai/adapters/litellm_utils/litellm_streaming.py b/libs/core/kiln_ai/adapters/litellm_utils/litellm_streaming.py
new file mode 100644
index 000000000..68b29dd62
--- /dev/null
+++ b/libs/core/kiln_ai/adapters/litellm_utils/litellm_streaming.py
@@ -0,0 +1,60 @@
+from __future__ import annotations
+
+from typing import Any, AsyncIterator, Optional, Union
+
+import litellm
+from litellm.types.utils import (
+    ModelResponse,
+    ModelResponseStream,
+    TextCompletionResponse,
+)
+
+
+class StreamingCompletion:
+    """
+    Async iterable wrapper around ``litellm.acompletion`` with streaming.
+
+    Yields ``ModelResponseStream`` chunks as they arrive.  After iteration
+    completes, the assembled ``ModelResponse`` is available via the
+    ``.response`` property.
+
+    Usage::
+
+        stream = StreamingCompletion(model=..., messages=...)
+        async for chunk in stream:
+            # handle chunk however you like (print, log, send over WS, …)
+            pass
+        final = stream.response   # fully assembled ModelResponse
+    """
+
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
+        kwargs = dict(kwargs)
+        kwargs.pop("stream", None)
+        self._args = args
+        self._kwargs = kwargs
+        self._response: Optional[Union[ModelResponse, TextCompletionResponse]] = None
+        self._iterated: bool = False
+
+    @property
+    def response(self) -> Optional[Union[ModelResponse, TextCompletionResponse]]:
+        """The final assembled response. Only available after iteration."""
+        if not self._iterated:
+            raise RuntimeError(
+                "StreamingCompletion has not been iterated yet. "
+                "Use 'async for chunk in stream:' before accessing .response"
+            )
+        return self._response
+
+    async def __aiter__(self) -> AsyncIterator[ModelResponseStream]:
+        self._response = None
+        self._iterated = False
+
+        chunks: list[ModelResponseStream] = []
+        stream = await litellm.acompletion(*self._args, stream=True, **self._kwargs)
+
+        async for chunk in stream:
+            chunks.append(chunk)
+            yield chunk
+
+        self._response = litellm.stream_chunk_builder(chunks)
+        self._iterated = True
diff --git a/libs/core/kiln_ai/adapters/litellm_utils/test_litellm_streaming.py b/libs/core/kiln_ai/adapters/litellm_utils/test_litellm_streaming.py
new file mode 100644
index 000000000..e35a51982
--- /dev/null
+++ b/libs/core/kiln_ai/adapters/litellm_utils/test_litellm_streaming.py
@@ -0,0 +1,139 @@
+from __future__ import annotations
+
+from types import SimpleNamespace
+from typing import Any, List
+from unittest.mock import MagicMock, patch
+
+import pytest
+
+from kiln_ai.adapters.litellm_utils.litellm_streaming import StreamingCompletion
+
+
+def _make_chunk(content: str | None = None, finish_reason: str | None = None) -> Any:
+    """Build a minimal chunk object matching litellm's streaming shape."""
+    delta = SimpleNamespace(content=content, role="assistant")
+    choice = SimpleNamespace(delta=delta, finish_reason=finish_reason, index=0)
+    return SimpleNamespace(choices=[choice], id="chatcmpl-test", model="test-model")
+
+
+async def _async_iter(items: List[Any]):
+    """Turn a plain list into an async iterator."""
+    for item in items:
+        yield item
+
+
+@pytest.fixture
+def mock_acompletion():
+    with patch("litellm.acompletion") as mock:
+        yield mock
+
+
+@pytest.fixture
+def mock_chunk_builder():
+    with patch("litellm.stream_chunk_builder") as mock:
+        yield mock
+
+
+class TestStreamingCompletion:
+    async def test_yields_all_chunks(self, mock_acompletion, mock_chunk_builder):
+        chunks = [_make_chunk("Hello"), _make_chunk(" world"), _make_chunk("!")]
+        mock_acompletion.return_value = _async_iter(chunks)
+        mock_chunk_builder.return_value = MagicMock(name="final_response")
+
+        stream = StreamingCompletion(model="test", messages=[])
+        received = [chunk async for chunk in stream]
+
+        assert received == chunks
+
+    async def test_response_available_after_iteration(
+        self, mock_acompletion, mock_chunk_builder
+    ):
+        chunks = [_make_chunk("hi")]
+        mock_acompletion.return_value = _async_iter(chunks)
+        sentinel = MagicMock(name="final_response")
+        mock_chunk_builder.return_value = sentinel
+
+        stream = StreamingCompletion(model="test", messages=[])
+        async for _ in stream:
+            pass
+
+        assert stream.response is sentinel
+
+    async def test_response_raises_before_iteration(self):
+        stream = StreamingCompletion(model="test", messages=[])
+        with pytest.raises(RuntimeError, match="not been iterated"):
+            _ = stream.response
+
+    async def test_stream_kwarg_is_stripped(self, mock_acompletion, mock_chunk_builder):
+        mock_acompletion.return_value = _async_iter([])
+        mock_chunk_builder.return_value = None
+
+        stream = StreamingCompletion(model="test", messages=[], stream=False)
+        async for _ in stream:
+            pass
+
+        _, call_kwargs = mock_acompletion.call_args
+        assert call_kwargs["stream"] is True
+
+    async def test_passes_args_and_kwargs_through(
+        self, mock_acompletion, mock_chunk_builder
+    ):
+        mock_acompletion.return_value = _async_iter([])
+        mock_chunk_builder.return_value = None
+
+        stream = StreamingCompletion(
+            model="gpt-4", messages=[{"role": "user", "content": "hi"}], temperature=0.5
+        )
+        async for _ in stream:
+            pass
+
+        _, call_kwargs = mock_acompletion.call_args
+        assert call_kwargs["model"] == "gpt-4"
+        assert call_kwargs["messages"] == [{"role": "user", "content": "hi"}]
+        assert call_kwargs["temperature"] == 0.5
+        assert call_kwargs["stream"] is True
+
+    async def test_chunks_passed_to_builder(self, mock_acompletion, mock_chunk_builder):
+        chunks = [_make_chunk("a"), _make_chunk("b")]
+        mock_acompletion.return_value = _async_iter(chunks)
+        mock_chunk_builder.return_value = MagicMock()
+
+        stream = StreamingCompletion(model="test", messages=[])
+        async for _ in stream:
+            pass
+
+        mock_chunk_builder.assert_called_once_with(chunks)
+
+    async def test_re_iteration_resets_state(
+        self, mock_acompletion, mock_chunk_builder
+    ):
+        first_chunks = [_make_chunk("first")]
+        second_chunks = [_make_chunk("second")]
+        first_response = MagicMock(name="first_response")
+        second_response = MagicMock(name="second_response")
+
+        mock_acompletion.side_effect = [
+            _async_iter(first_chunks),
+            _async_iter(second_chunks),
+        ]
+        mock_chunk_builder.side_effect = [first_response, second_response]
+
+        stream = StreamingCompletion(model="test", messages=[])
+
+        async for _ in stream:
+            pass
+        assert stream.response is first_response
+
+        async for _ in stream:
+            pass
+        assert stream.response is second_response
+
+    async def test_empty_stream(self, mock_acompletion, mock_chunk_builder):
+        mock_acompletion.return_value = _async_iter([])
+        mock_chunk_builder.return_value = None
+
+        stream = StreamingCompletion(model="test", messages=[])
+        received = [chunk async for chunk in stream]
+
+        assert received == []
+        assert stream.response is None
diff --git a/libs/core/kiln_ai/adapters/model_adapters/adapter_stream.py b/libs/core/kiln_ai/adapters/model_adapters/adapter_stream.py
new file mode 100644
index 000000000..db4c4642a
--- /dev/null
+++ b/libs/core/kiln_ai/adapters/model_adapters/adapter_stream.py
@@ -0,0 +1,291 @@
+from __future__ import annotations
+
+import copy
+import json
+import logging
+from dataclasses import dataclass
+from typing import TYPE_CHECKING, Any, AsyncIterator
+
+from litellm.types.utils import (
+    ChatCompletionMessageToolCall,
+    Choices,
+    ModelResponse,
+)
+
+from kiln_ai.adapters.chat import ChatCompletionMessageIncludingLiteLLM
+from kiln_ai.adapters.chat.chat_formatter import ChatFormatter
+from kiln_ai.adapters.litellm_utils.litellm_streaming import StreamingCompletion
+from kiln_ai.adapters.ml_model_list import KilnModelProvider
+from kiln_ai.adapters.model_adapters.stream_events import (
+    AdapterStreamEvent,
+    ToolCallEvent,
+    ToolCallEventType,
+)
+from kiln_ai.adapters.run_output import RunOutput
+from kiln_ai.datamodel import Usage
+
+if TYPE_CHECKING:
+    from kiln_ai.adapters.model_adapters.litellm_adapter import LiteLlmAdapter
+
+MAX_CALLS_PER_TURN = 10
+MAX_TOOL_CALLS_PER_TURN = 30
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass
+class AdapterStreamResult:
+    run_output: RunOutput
+    usage: Usage
+
+
+class AdapterStream:
+    """
+    Orchestrates a full task execution as an async iterator,
+    composing StreamingCompletion instances across chat turns and tool-call rounds.
+
+    Yields ``ModelResponseStream`` chunks from each LLM call and
+    ``ToolCallEvent`` instances between tool-call rounds.
+
+    After iteration completes the ``result`` property provides the
+    ``AdapterStreamResult`` with the final ``RunOutput`` and ``Usage``.
+    """
+
+    def __init__(
+        self,
+        adapter: LiteLlmAdapter,
+        provider: KilnModelProvider,
+        chat_formatter: ChatFormatter,
+        initial_messages: list[ChatCompletionMessageIncludingLiteLLM],
+        top_logprobs: int | None,
+    ) -> None:
+        self._adapter = adapter
+        self._provider = provider
+        self._chat_formatter = chat_formatter
+        self._messages = initial_messages
+        self._top_logprobs = top_logprobs
+        self._result: AdapterStreamResult | None = None
+        self._iterated = False
+
+    @property
+    def result(self) -> AdapterStreamResult:
+        if not self._iterated:
+            raise RuntimeError(
+                "AdapterStream has not been iterated yet. "
+                "Use 'async for event in stream:' before accessing .result"
+            )
+        if self._result is None:
+            raise RuntimeError("AdapterStream completed without producing a result")
+        return self._result
+
+    async def __aiter__(self) -> AsyncIterator[AdapterStreamEvent]:
+        self._result = None
+        self._iterated = False
+
+        usage = Usage()
+        prior_output: str | None = None
+        final_choice: Choices | None = None
+        turns = 0
+
+        while True:
+            turns += 1
+            if turns > MAX_CALLS_PER_TURN:
+                raise RuntimeError(
+                    f"Too many turns ({turns}). Stopping iteration to avoid using too many tokens."
+                )
+
+            turn = self._chat_formatter.next_turn(prior_output)
+            if turn is None:
+                break
+
+            for message in turn.messages:
+                if message.content is None:
+                    raise ValueError("Empty message content isn't allowed")
+                self._messages.append(
+                    {"role": message.role, "content": message.content}  # type: ignore[arg-type]
+                )
+
+            skip_response_format = not turn.final_call
+            turn_top_logprobs = self._top_logprobs if turn.final_call else None
+
+            async for event in self._stream_model_turn(
+                skip_response_format, turn_top_logprobs
+            ):
+                if isinstance(event, _ModelTurnComplete):
+                    usage += event.usage
+                    prior_output = event.assistant_message
+                    final_choice = event.model_choice
+                else:
+                    yield event
+
+            if not prior_output:
+                raise RuntimeError("No assistant message/output returned from model")
+
+        logprobs = self._adapter._extract_and_validate_logprobs(final_choice)
+
+        intermediate_outputs = self._chat_formatter.intermediate_outputs()
+        self._adapter._extract_reasoning_to_intermediate_outputs(
+            final_choice, intermediate_outputs
+        )
+
+        if not isinstance(prior_output, str):
+            raise RuntimeError(f"assistant message is not a string: {prior_output}")
+
+        trace = self._adapter.all_messages_to_trace(self._messages)
+        self._result = AdapterStreamResult(
+            run_output=RunOutput(
+                output=prior_output,
+                intermediate_outputs=intermediate_outputs,
+                output_logprobs=logprobs,
+                trace=trace,
+            ),
+            usage=usage,
+        )
+        self._iterated = True
+
+    async def _stream_model_turn(
+        self,
+        skip_response_format: bool,
+        top_logprobs: int | None,
+    ) -> AsyncIterator[AdapterStreamEvent | _ModelTurnComplete]:
+        usage = Usage()
+        tool_calls_count = 0
+
+        while tool_calls_count < MAX_TOOL_CALLS_PER_TURN:
+            completion_kwargs = await self._adapter.build_completion_kwargs(
+                self._provider,
+                copy.deepcopy(self._messages),
+                top_logprobs,
+                skip_response_format,
+            )
+
+            stream = StreamingCompletion(**completion_kwargs)
+            async for chunk in stream:
+                yield chunk
+
+            response, response_choice = _validate_response(stream.response)
+            usage += self._adapter.usage_from_response(response)
+
+            content = response_choice.message.content
+            tool_calls = response_choice.message.tool_calls
+            if not content and not tool_calls:
+                raise ValueError(
+                    "Model returned an assistant message, but no content or tool calls. This is not supported."
+                )
+
+            self._messages.append(response_choice.message)
+
+            if tool_calls and len(tool_calls) > 0:
+                async for event in self._handle_tool_calls(tool_calls):
+                    yield event
+
+                assistant_msg = self._extract_task_response(tool_calls)
+                if assistant_msg is not None:
+                    yield _ModelTurnComplete(
+                        assistant_message=assistant_msg,
+                        model_choice=response_choice,
+                        usage=usage,
+                    )
+                    return
+
+                tool_calls_count += 1
+                continue
+
+            if content:
+                yield _ModelTurnComplete(
+                    assistant_message=content,
+                    model_choice=response_choice,
+                    usage=usage,
+                )
+                return
+
+            raise RuntimeError(
+                "Model returned neither content nor tool calls. It must return at least one of these."
+            )
+
+        raise RuntimeError(
+            f"Too many tool calls ({tool_calls_count}). Stopping iteration to avoid using too many tokens."
+        )
+
+    async def _handle_tool_calls(
+        self,
+        tool_calls: list[ChatCompletionMessageToolCall],
+    ) -> AsyncIterator[AdapterStreamEvent]:
+        real_tool_calls = [
+            tc for tc in tool_calls if tc.function.name != "task_response"
+        ]
+
+        for tc in real_tool_calls:
+            try:
+                parsed_args = json.loads(tc.function.arguments)
+            except (json.JSONDecodeError, TypeError):
+                parsed_args = None
+
+            yield ToolCallEvent(
+                event_type=ToolCallEventType.INPUT_AVAILABLE,
+                tool_call_id=tc.id,
+                tool_name=tc.function.name or "unknown",
+                arguments=parsed_args,
+                error=(
+                    f"Failed to parse arguments: {tc.function.arguments}"
+                    if parsed_args is None
+                    else None
+                ),
+            )
+
+        _, tool_msgs = await self._adapter.process_tool_calls(tool_calls)
+
+        for tool_msg in tool_msgs:
+            tc_id = tool_msg["tool_call_id"]
+            tc_name = _find_tool_name(tool_calls, tc_id)
+            content = tool_msg["content"]
+            yield ToolCallEvent(
+                event_type=ToolCallEventType.OUTPUT_AVAILABLE,
+                tool_call_id=tc_id,
+                tool_name=tc_name,
+                result=str(content) if content is not None else None,
+            )
+
+        self._messages.extend(tool_msgs)
+
+    @staticmethod
+    def _extract_task_response(
+        tool_calls: list[ChatCompletionMessageToolCall],
+    ) -> str | None:
+        for tc in tool_calls:
+            if tc.function.name == "task_response":
+                return tc.function.arguments
+        return None
+
+
+@dataclass
+class _ModelTurnComplete:
+    """Internal sentinel yielded when a model turn finishes."""
+
+    assistant_message: str
+    model_choice: Choices | None
+    usage: Usage
+
+
+def _validate_response(
+    response: Any,
+) -> tuple[ModelResponse, Choices]:
+    if (
+        not isinstance(response, ModelResponse)
+        or not response.choices
+        or len(response.choices) == 0
+        or not isinstance(response.choices[0], Choices)
+    ):
+        raise RuntimeError(
+            f"Expected ModelResponse with Choices, got {type(response)}."
+        )
+    return response, response.choices[0]
+
+
+def _find_tool_name(
+    tool_calls: list[ChatCompletionMessageToolCall], tool_call_id: str
+) -> str:
+    for tc in tool_calls:
+        if tc.id == tool_call_id:
+            return tc.function.name or "unknown"
+    return "unknown"
diff --git a/libs/core/kiln_ai/adapters/model_adapters/base_adapter.py b/libs/core/kiln_ai/adapters/model_adapters/base_adapter.py
index 7cda8c6dc..d9633ac81 100644
--- a/libs/core/kiln_ai/adapters/model_adapters/base_adapter.py
+++ b/libs/core/kiln_ai/adapters/model_adapters/base_adapter.py
@@ -1,7 +1,12 @@
+from __future__ import annotations
+
 import json
+import uuid
 from abc import ABCMeta, abstractmethod
 from dataclasses import dataclass
-from typing import Dict, Tuple
+from typing import TYPE_CHECKING, AsyncIterator, Dict, Tuple
+
+from litellm.types.utils import ModelResponseStream
 
 from kiln_ai.adapters.chat.chat_formatter import (
     ChatFormatter,
@@ -13,6 +18,13 @@
     StructuredOutputMode,
     default_structured_output_mode_for_model_provider,
 )
+from kiln_ai.adapters.model_adapters.adapter_stream import AdapterStreamResult
+from kiln_ai.adapters.model_adapters.stream_events import (
+    AiSdkEventType,
+    AiSdkStreamConverter,
+    AiSdkStreamEvent,
+    ToolCallEvent,
+)
 from kiln_ai.adapters.parsers.json_parser import parse_json_string
 from kiln_ai.adapters.parsers.parser_registry import model_parser_from_id
 from kiln_ai.adapters.parsers.request_formatters import request_formatter_from_id
@@ -49,6 +61,9 @@
 from kiln_ai.utils.exhaustive_error import raise_exhaustive_enum_error
 from kiln_ai.utils.open_ai_types import ChatCompletionMessageParam
 
+if TYPE_CHECKING:
+    from kiln_ai.adapters.model_adapters.adapter_stream import AdapterStream
+
 
 @dataclass
 class AdapterConfig:
@@ -127,10 +142,10 @@ async def invoke(
         self,
         input: InputType,
         input_source: DataSource | None = None,
-        existing_run: TaskRun | None = None,
+        prior_trace: list[ChatCompletionMessageParam] | None = None,
     ) -> TaskRun:
         run_output, _ = await self.invoke_returning_run_output(
-            input, input_source, existing_run
+            input, input_source, prior_trace
         )
         return run_output
 
@@ -138,7 +153,7 @@ async def _run_returning_run_output(
         self,
         input: InputType,
         input_source: DataSource | None = None,
-        existing_run: TaskRun | None = None,
+        prior_trace: list[ChatCompletionMessageParam] | None = None,
     ) -> Tuple[TaskRun, RunOutput]:
         # validate input, allowing arrays
         if self.input_schema is not None:
@@ -149,14 +164,7 @@ async def _run_returning_run_output(
                 require_object=False,
             )
 
-        if existing_run is not None and (
-            not existing_run.trace or len(existing_run.trace) == 0
-        ):
-            raise ValueError(
-                "Run has no trace. Cannot continue session without conversation history."
-            )
-
-        prior_trace = existing_run.trace if existing_run else None
+        prior_trace = prior_trace if prior_trace else None
 
         # Format model input for model call (we save the original input in the task without formatting)
         formatted_input = input
@@ -215,28 +223,9 @@ async def _run_returning_run_output(
                 "Reasoning is required for this model, but no reasoning was returned."
             )
 
-        # Create the run and output - merge if there is an existing run
-        if existing_run is not None:
-            merged_output = RunOutput(
-                output=parsed_output.output,
-                intermediate_outputs=parsed_output.intermediate_outputs
-                or run_output.intermediate_outputs,
-                output_logprobs=parsed_output.output_logprobs
-                or run_output.output_logprobs,
-                trace=run_output.trace,
-            )
-            run = self.generate_run(
-                input,
-                input_source,
-                merged_output,
-                usage,
-                run_output.trace,
-                existing_run=existing_run,
-            )
-        else:
-            run = self.generate_run(
-                input, input_source, parsed_output, usage, run_output.trace
-            )
+        run = self.generate_run(
+            input, input_source, parsed_output, usage, run_output.trace
+        )
 
         # Save the run if configured to do so, and we have a path to save to
         if (
@@ -245,7 +234,7 @@ async def _run_returning_run_output(
             and self.task.path is not None
         ):
             run.save_to_file()
-        elif existing_run is None:
+        else:
             # Clear the ID to indicate it's not persisted
             run.id = None
 
@@ -255,7 +244,7 @@ async def invoke_returning_run_output(
         self,
         input: InputType,
         input_source: DataSource | None = None,
-        existing_run: TaskRun | None = None,
+        prior_trace: list[ChatCompletionMessageParam] | None = None,
     ) -> Tuple[TaskRun, RunOutput]:
         # Determine if this is the root agent (no existing run context)
         is_root_agent = get_agent_run_id() is None
@@ -266,7 +255,7 @@ async def invoke_returning_run_output(
 
         try:
             return await self._run_returning_run_output(
-                input, input_source, existing_run
+                input, input_source, prior_trace
             )
         finally:
             if is_root_agent:
@@ -277,6 +266,134 @@ async def invoke_returning_run_output(
                 finally:
                     clear_agent_run_id()
 
+    def invoke_openai_stream(
+        self,
+        input: InputType,
+        input_source: DataSource | None = None,
+        prior_trace: list[ChatCompletionMessageParam] | None = None,
+    ) -> OpenAIStreamResult:
+        """Stream raw OpenAI-protocol chunks for the task execution.
+
+        Returns an async-iterable that yields ``ModelResponseStream`` chunks
+        as they arrive from the model.  After the iterator is exhausted the
+        run has been validated and saved (when configured).  The resulting
+        ``TaskRun`` is available via the ``.task_run`` property.
+
+        Tool-call rounds happen internally and are not surfaced; use
+        ``invoke_ai_sdk_stream`` if you need tool-call events.
+        """
+        return OpenAIStreamResult(self, input, input_source, prior_trace)
+
+    def invoke_ai_sdk_stream(
+        self,
+        input: InputType,
+        input_source: DataSource | None = None,
+        prior_trace: list[ChatCompletionMessageParam] | None = None,
+    ) -> AiSdkStreamResult:
+        """Stream AI SDK protocol events for the task execution.
+
+        Returns an async-iterable that yields ``AiSdkStreamEvent`` instances
+        covering text, reasoning, tool-call lifecycle, step boundaries, and
+        control events.  After the iterator is exhausted the resulting
+        ``TaskRun`` is available via the ``.task_run`` property.
+        """
+        return AiSdkStreamResult(self, input, input_source, prior_trace)
+
+    def _prepare_stream(
+        self,
+        input: InputType,
+        prior_trace: list[ChatCompletionMessageParam] | None,
+    ) -> AdapterStream:
+        if self.input_schema is not None:
+            validate_schema_with_value_error(
+                input,
+                self.input_schema,
+                "This task requires a specific input schema. While the model produced JSON, that JSON didn't meet the schema. Search 'Troubleshooting Structured Data Issues' in our docs for more information.",
+                require_object=False,
+            )
+
+        prior_trace = prior_trace if prior_trace else None
+
+        formatted_input = input
+        formatter_id = self.model_provider().formatter
+        if formatter_id is not None:
+            formatter = request_formatter_from_id(formatter_id)
+            formatted_input = formatter.format_input(input)
+
+        return self._create_run_stream(formatted_input, prior_trace)
+
+    def _finalize_stream(
+        self,
+        adapter_stream: AdapterStream,
+        input: InputType,
+        input_source: DataSource | None,
+        prior_trace: list[ChatCompletionMessageParam] | None,
+    ) -> TaskRun:
+        """Streaming invocations are only concerned with passing through events as they come in.
+        At the end of the stream, we still need to validate the output, create a run and everything
+        else that a non-streaming invocation would do.
+        """
+
+        result: AdapterStreamResult = adapter_stream.result
+        run_output = result.run_output
+        usage = result.usage
+
+        provider = self.model_provider()
+        parser = model_parser_from_id(provider.parser)
+        parsed_output = parser.parse_output(original_output=run_output)
+
+        if self.output_schema is not None:
+            if isinstance(parsed_output.output, str):
+                parsed_output.output = parse_json_string(parsed_output.output)
+            if not isinstance(parsed_output.output, dict):
+                raise RuntimeError(
+                    f"structured response is not a dict: {parsed_output.output}"
+                )
+            validate_schema_with_value_error(
+                parsed_output.output,
+                self.output_schema,
+                "This task requires a specific output schema. While the model produced JSON, that JSON didn't meet the schema. Search 'Troubleshooting Structured Data Issues' in our docs for more information.",
+            )
+        else:
+            if not isinstance(parsed_output.output, str):
+                raise RuntimeError(
+                    f"response is not a string for non-structured task: {parsed_output.output}"
+                )
+
+        trace_has_toolcalls = parsed_output.trace is not None and any(
+            message.get("role", None) == "tool" for message in parsed_output.trace
+        )
+        if (
+            provider.reasoning_capable
+            and (
+                not parsed_output.intermediate_outputs
+                or "reasoning" not in parsed_output.intermediate_outputs
+            )
+            and not (
+                provider.reasoning_optional_for_structured_output
+                and self.has_structured_output()
+            )
+            and not trace_has_toolcalls
+        ):
+            raise RuntimeError(
+                "Reasoning is required for this model, but no reasoning was returned."
+            )
+
+        run = self.generate_run(
+            input, input_source, parsed_output, usage, run_output.trace
+        )
+
+        if (
+            self.base_adapter_config.allow_saving
+            and Config.shared().autosave_runs
+            and self.task.path is not None
+        ):
+            run.save_to_file()
+        else:
+            run.id = None
+
+        return run
+
     def has_structured_output(self) -> bool:
         return self.output_schema is not None
 
@@ -292,6 +409,14 @@ async def _run(
     ) -> Tuple[RunOutput, Usage | None]:
         pass
 
+    def _create_run_stream(
+        self,
+        input: InputType,
+        prior_trace: list[ChatCompletionMessageParam] | None = None,
+    ) -> AdapterStream:
+        """Create a stream for the adapter. Implementations must override this method to support streaming."""
+        raise NotImplementedError("Streaming is not supported for this adapter type")
+
     def build_prompt(self) -> str:
         if self.prompt_builder is None:
             raise ValueError("Prompt builder is not available for MCP run config")
@@ -372,7 +497,6 @@ def generate_run(
         run_output: RunOutput,
         usage: Usage | None = None,
         trace: list[ChatCompletionMessageParam] | None = None,
-        existing_run: TaskRun | None = None,
     ) -> TaskRun:
         output_str = (
             json.dumps(run_output.output, ensure_ascii=False)
@@ -395,26 +519,6 @@ def generate_run(
             ),
         )
 
-        if existing_run is not None:
-            accumulated_usage = existing_run.usage
-            if usage is not None:
-                if accumulated_usage is not None:
-                    accumulated_usage = accumulated_usage + usage
-                else:
-                    accumulated_usage = usage
-
-            merged_intermediate = dict(existing_run.intermediate_outputs or {})
-            if run_output.intermediate_outputs:
-                for k, v in run_output.intermediate_outputs.items():
-                    merged_intermediate[k] = v
-
-            existing_run.output = new_output
-            existing_run.trace = trace
-            existing_run.usage = accumulated_usage
-            existing_run.intermediate_outputs = merged_intermediate
-
-            return existing_run
-
         # Convert input and output to JSON strings if they aren't strings
         input_str = (
             input if isinstance(input, str) else json.dumps(input, ensure_ascii=False)
@@ -503,3 +607,137 @@ async def available_tools(self) -> list[KilnToolInterface]:
             )
 
         return tools
+
+
+class OpenAIStreamResult:
+    """Async-iterable wrapper around the OpenAI streaming flow.
+
+    Yields ``ModelResponseStream`` chunks.  After iteration the resulting
+    ``TaskRun`` is available via the ``.task_run`` property.
+    """
+
+    def __init__(
+        self,
+        adapter: BaseAdapter,
+        input: InputType,
+        input_source: DataSource | None,
+        prior_trace: list[ChatCompletionMessageParam] | None,
+    ) -> None:
+        self._adapter = adapter
+        self._input = input
+        self._input_source = input_source
+        self._prior_trace = prior_trace
+        self._task_run: TaskRun | None = None
+
+    @property
+    def task_run(self) -> TaskRun:
+        if self._task_run is None:
+            raise RuntimeError(
+                "Stream has not been fully consumed yet. "
+                "Iterate over the stream before accessing .task_run"
+            )
+        return self._task_run
+
+    async def __aiter__(self) -> AsyncIterator[ModelResponseStream]:
+        self._task_run = None
+        is_root_agent = get_agent_run_id() is None
+        if is_root_agent:
+            set_agent_run_id(generate_agent_run_id())
+
+        try:
+            adapter_stream = self._adapter._prepare_stream(
+                self._input, self._prior_trace
+            )
+
+            async for event in adapter_stream:
+                if isinstance(event, ModelResponseStream):
+                    yield event
+
+            self._task_run = self._adapter._finalize_stream(
+                adapter_stream, self._input, self._input_source, self._prior_trace
+            )
+        finally:
+            if is_root_agent:
+                try:
+                    run_id = get_agent_run_id()
+                    if run_id:
+                        await MCPSessionManager.shared().cleanup_session(run_id)
+                finally:
+                    clear_agent_run_id()
+
+
+class AiSdkStreamResult:
+    """Async-iterable wrapper around the AI SDK streaming flow.
+
+    Yields ``AiSdkStreamEvent`` instances.  After iteration the resulting
+    ``TaskRun`` is available via the ``.task_run`` property.
+    """
+
+    def __init__(
+        self,
+        adapter: BaseAdapter,
+        input: InputType,
+        input_source: DataSource | None,
+        prior_trace: list[ChatCompletionMessageParam] | None,
+    ) -> None:
+        self._adapter = adapter
+        self._input = input
+        self._input_source = input_source
+        self._prior_trace = prior_trace
+        self._task_run: TaskRun | None = None
+
+    @property
+    def task_run(self) -> TaskRun:
+        if self._task_run is None:
+            raise RuntimeError(
+                "Stream has not been fully consumed yet. "
+                "Iterate over the stream before accessing .task_run"
+            )
+        return self._task_run
+
+    async def __aiter__(self) -> AsyncIterator[AiSdkStreamEvent]:
+        self._task_run = None
+        is_root_agent = get_agent_run_id() is None
+        if is_root_agent:
+            set_agent_run_id(generate_agent_run_id())
+
+        try:
+            adapter_stream = self._adapter._prepare_stream(
+                self._input, self._prior_trace
+            )
+
+            message_id = f"msg-{uuid.uuid4().hex}"
+            converter = AiSdkStreamConverter()
+
+            yield AiSdkStreamEvent(AiSdkEventType.START, {"messageId": message_id})
+            yield AiSdkStreamEvent(AiSdkEventType.START_STEP)
+
+            last_event_was_tool_call = False
+            async for event in adapter_stream:
+                if isinstance(event, ModelResponseStream):
+                    if last_event_was_tool_call:
+                        converter.reset_for_next_step()
+                        last_event_was_tool_call = False
+                    for ai_event in converter.convert_chunk(event):
+                        yield ai_event
+                elif isinstance(event, ToolCallEvent):
+                    last_event_was_tool_call = True
+                    for ai_event in converter.convert_tool_event(event):
+                        yield ai_event
+
+            for ai_event in converter.finalize():
+                yield ai_event
+
+            yield AiSdkStreamEvent(AiSdkEventType.FINISH_STEP)
+
+            self._task_run = self._adapter._finalize_stream(
+                adapter_stream, self._input, self._input_source, self._prior_trace
+            )
+        finally:
+            if is_root_agent:
+                try:
+                    run_id = get_agent_run_id()
+                    if run_id:
+                        await MCPSessionManager.shared().cleanup_session(run_id)
+                finally:
+                    clear_agent_run_id()
diff --git a/libs/core/kiln_ai/adapters/model_adapters/litellm_adapter.py b/libs/core/kiln_ai/adapters/model_adapters/litellm_adapter.py
index 131be097c..cebccdf57 100644
--- a/libs/core/kiln_ai/adapters/model_adapters/litellm_adapter.py
+++ b/libs/core/kiln_ai/adapters/model_adapters/litellm_adapter.py
@@ -25,6 +25,7 @@
     ModelProviderName,
     StructuredOutputMode,
 )
+from kiln_ai.adapters.model_adapters.adapter_stream import AdapterStream
 from kiln_ai.adapters.model_adapters.base_adapter import (
     AdapterConfig,
     BaseAdapter,
@@ -261,6 +262,28 @@ async def _run(
 
         return output, usage
 
+    def _create_run_stream(
+        self,
+        input: InputType,
+        prior_trace: list[ChatCompletionMessageParam] | None = None,
+    ) -> AdapterStream:
+        provider = self.model_provider()
+        if not provider.model_id:
+            raise ValueError("Model ID is required for OpenAI compatible models")
+
+        chat_formatter = self.build_chat_formatter(input, prior_trace)
+        initial_messages: list[ChatCompletionMessageIncludingLiteLLM] = copy.deepcopy(
+            chat_formatter.initial_messages()
+        )
+
+        return AdapterStream(
+            adapter=self,
+            provider=provider,
+            chat_formatter=chat_formatter,
+            initial_messages=initial_messages,
+            top_logprobs=self.base_adapter_config.top_logprobs,
+        )
+
     def _extract_and_validate_logprobs(
         self, final_choice: Choices | None
     ) -> ChoiceLogprobs | None:
@@ -297,9 +320,10 @@ def _extract_reasoning_to_intermediate_outputs(
                     intermediate_outputs["reasoning"] = stripped_reasoning_content
 
     async def acompletion_checking_response(
-        self, **kwargs
+        self, **kwargs: Any
     ) -> Tuple[ModelResponse, Choices]:
         response = await litellm.acompletion(**kwargs)
+
         if (
             not isinstance(response, ModelResponse)
             or not response.choices
diff --git a/libs/core/kiln_ai/adapters/model_adapters/mcp_adapter.py b/libs/core/kiln_ai/adapters/model_adapters/mcp_adapter.py
index 45aabc53e..c488e7fc0 100644
--- a/libs/core/kiln_ai/adapters/model_adapters/mcp_adapter.py
+++ b/libs/core/kiln_ai/adapters/model_adapters/mcp_adapter.py
@@ -1,7 +1,10 @@
 import json
 from typing import Tuple
 
-from kiln_ai.adapters.model_adapters.base_adapter import AdapterConfig, BaseAdapter
+from kiln_ai.adapters.model_adapters.base_adapter import (
+    AdapterConfig,
+    BaseAdapter,
+)
 from kiln_ai.adapters.parsers.json_parser import parse_json_string
 from kiln_ai.adapters.run_output import RunOutput
 from kiln_ai.datamodel import DataSource, Task, TaskRun, Usage
@@ -85,16 +88,16 @@ async def invoke(
         self,
         input: InputType,
         input_source: DataSource | None = None,
-        existing_run: TaskRun | None = None,
+        prior_trace: list[ChatCompletionMessageParam] | None = None,
     ) -> TaskRun:
-        if existing_run is not None:
+        if prior_trace:
             raise NotImplementedError(
                 "Session continuation is not supported for MCP adapter. "
                 "MCP tools are single-turn and do not maintain conversation state."
             )
 
         run_output, _ = await self.invoke_returning_run_output(
-            input, input_source, existing_run
+            input, input_source, prior_trace
         )
         return run_output
 
@@ -102,13 +105,13 @@ async def invoke_returning_run_output(
         self,
         input: InputType,
         input_source: DataSource | None = None,
-        existing_run: TaskRun | None = None,
+        prior_trace: list[ChatCompletionMessageParam] | None = None,
     ) -> Tuple[TaskRun, RunOutput]:
         """
         Runs the task and returns both the persisted TaskRun and raw RunOutput.
         If this call is the root of a run, it creates an agent run context, ensures MCP tool calls have a valid session scope, and cleans up the session/context on completion.
         """
-        if existing_run is not None:
+        if prior_trace:
             raise NotImplementedError(
                 "Session continuation is not supported for MCP adapter. "
                 "MCP tools are single-turn and do not maintain conversation state."
diff --git a/libs/core/kiln_ai/adapters/model_adapters/stream_events.py b/libs/core/kiln_ai/adapters/model_adapters/stream_events.py
new file mode 100644
index 000000000..b2784484a
--- /dev/null
+++ b/libs/core/kiln_ai/adapters/model_adapters/stream_events.py
@@ -0,0 +1,290 @@
+from __future__ import annotations
+
+import uuid
+from dataclasses import dataclass, field
+from enum import Enum
+from typing import Any
+
+from litellm.types.utils import ModelResponseStream
+
+
+class AiSdkEventType(str, Enum):
+    START = "start"
+    FINISH = "finish"
+    ERROR = "error"
+    ABORT = "abort"
+
+    TEXT_START = "text-start"
+    TEXT_DELTA = "text-delta"
+    TEXT_END = "text-end"
+
+    REASONING_START = "reasoning-start"
+    REASONING_DELTA = "reasoning-delta"
+    REASONING_END = "reasoning-end"
+
+    TOOL_INPUT_START = "tool-input-start"
+    TOOL_INPUT_DELTA = "tool-input-delta"
+    TOOL_INPUT_AVAILABLE = "tool-input-available"
+    TOOL_INPUT_ERROR = "tool-input-error"
+
+    TOOL_OUTPUT_AVAILABLE = "tool-output-available"
+    TOOL_OUTPUT_ERROR = "tool-output-error"
+
+    START_STEP = "start-step"
+    FINISH_STEP = "finish-step"
+
+    METADATA = "metadata"
+    SOURCE_URL = "source-url"
+    SOURCE_DOCUMENT = "source-document"
+    FILE = "file"
+
+
+@dataclass
+class AiSdkStreamEvent:
+    type: AiSdkEventType
+    payload: dict[str, Any] = field(default_factory=dict)
+
+    def model_dump(self) -> dict[str, Any]:
+        return {
+            "type": self.type.value,
+            **self.payload,
+        }
+
+
+class ToolCallEventType(str, Enum):
+    INPUT_AVAILABLE = "input_available"
+    OUTPUT_AVAILABLE = "output_available"
+    OUTPUT_ERROR = "output_error"
+
+
+@dataclass
+class ToolCallEvent:
+    event_type: ToolCallEventType
+    tool_call_id: str
+    tool_name: str
+    arguments: dict[str, Any] | None = None
+    result: str | None = None
+    error: str | None = None
+
+
+AdapterStreamEvent = ModelResponseStream | ToolCallEvent
+
+
+class AiSdkStreamConverter:
+    """Stateful converter from OpenAI streaming chunks to AI SDK events."""
+
+    def __init__(self) -> None:
+        self._text_started = False
+        self._text_id = f"text-{uuid.uuid4().hex[:12]}"
+        self._reasoning_started = False
+        self._reasoning_id = f"reasoning-{uuid.uuid4().hex[:12]}"
+        self._reasoning_block_count = 0
+        self._tool_calls_state: dict[int, dict[str, Any]] = {}
+        self._finish_reason: str | None = None
+        self._usage_data: Any = None
+
+    def convert_chunk(self, chunk: ModelResponseStream) -> list[AiSdkStreamEvent]:
+        events: list[AiSdkStreamEvent] = []
+
+        for choice in chunk.choices:
+            if choice.finish_reason is not None:
+                self._finish_reason = choice.finish_reason
+
+            delta = choice.delta
+            if delta is None:
+                continue
+
+            reasoning_content = getattr(delta, "reasoning_content", None)
+            if reasoning_content is not None:
+                if not self._reasoning_started:
+                    self._reasoning_block_count += 1
+                    self._reasoning_id = f"reasoning-{uuid.uuid4().hex[:12]}"
+                    events.append(
+                        AiSdkStreamEvent(
+                            AiSdkEventType.REASONING_START,
+                            {"id": self._reasoning_id},
+                        )
+                    )
+                    self._reasoning_started = True
+                events.append(
+                    AiSdkStreamEvent(
+                        AiSdkEventType.REASONING_DELTA,
+                        {"id": self._reasoning_id, "delta": reasoning_content},
+                    )
+                )
+
+            if delta.content:
+                if self._reasoning_started:
+                    events.append(
+                        AiSdkStreamEvent(
+                            AiSdkEventType.REASONING_END,
+                            {"id": self._reasoning_id},
+                        )
+                    )
+                    self._reasoning_started = False
+
+                if not self._text_started:
+                    events.append(
+                        AiSdkStreamEvent(
+                            AiSdkEventType.TEXT_START,
+                            {"id": self._text_id},
+                        )
+                    )
+                    self._text_started = True
+                events.append(
+                    AiSdkStreamEvent(
+                        AiSdkEventType.TEXT_DELTA,
+                        {"id": self._text_id, "delta": delta.content},
+                    )
+                )
+
+            if delta.tool_calls:
+                if self._reasoning_started:
+                    events.append(
+                        AiSdkStreamEvent(
+                            AiSdkEventType.REASONING_END,
+                            {"id": self._reasoning_id},
+                        )
+                    )
+                    self._reasoning_started = False
+
+                for tc_delta in delta.tool_calls:
+                    idx = tc_delta.index
+                    tc_state = self._tool_calls_state.setdefault(
+                        idx,
+                        {
+                            "id": None,
+                            "name": None,
+                            "arguments": "",
+                            "started": False,
+                        },
+                    )
+
+                    if tc_delta.id is not None:
+                        tc_state["id"] = tc_delta.id
+
+                    func = getattr(tc_delta, "function", None)
+                    if func is not None:
+                        if func.name is not None:
+                            tc_state["name"] = func.name
+                        if func.arguments:
+                            tc_state["arguments"] += func.arguments
+
+                    if tc_state["id"] and tc_state["name"] and not tc_state["started"]:
+                        events.append(
+                            AiSdkStreamEvent(
+                                AiSdkEventType.TOOL_INPUT_START,
+                                {
+                                    "toolCallId": tc_state["id"],
+                                    "toolName": tc_state["name"],
+                                },
+                            )
+                        )
+                        tc_state["started"] = True
+
+                    if func and func.arguments and tc_state["id"]:
+                        events.append(
+                            AiSdkStreamEvent(
+                                AiSdkEventType.TOOL_INPUT_DELTA,
+                                {
+                                    "toolCallId": tc_state["id"],
+                                    "inputTextDelta": func.arguments,
+                                },
+                            )
+                        )
+
+        if not chunk.choices:
+            usage = getattr(chunk, "usage", None)
+            if usage is not None:
+                self._usage_data = usage
+
+        return events
+
+    def convert_tool_event(self, event: ToolCallEvent) -> list[AiSdkStreamEvent]:
+        events: list[AiSdkStreamEvent] = []
+
+        if event.event_type == ToolCallEventType.INPUT_AVAILABLE:
+            events.append(
+                AiSdkStreamEvent(
+                    AiSdkEventType.TOOL_INPUT_AVAILABLE,
+                    {
+                        "toolCallId": event.tool_call_id,
+                        "toolName": event.tool_name,
+                        "input": event.arguments or {},
+                    },
+                )
+            )
+        elif event.event_type == ToolCallEventType.OUTPUT_AVAILABLE:
+            events.append(
+                AiSdkStreamEvent(
+                    AiSdkEventType.TOOL_OUTPUT_AVAILABLE,
+                    {
+                        "toolCallId": event.tool_call_id,
+                        "output": event.result,
+                    },
+                )
+            )
+        elif event.event_type == ToolCallEventType.OUTPUT_ERROR:
+            events.append(
+                AiSdkStreamEvent(
+                    AiSdkEventType.TOOL_OUTPUT_ERROR,
+                    {
+                        "toolCallId": event.tool_call_id,
+                        "errorText": event.error or "Unknown error",
+                    },
+                )
+            )
+
+        return events
+
+    def finalize(self) -> list[AiSdkStreamEvent]:
+        events: list[AiSdkStreamEvent] = []
+
+        if self._reasoning_started:
+            events.append(
+                AiSdkStreamEvent(
+                    AiSdkEventType.REASONING_END,
+                    {"id": self._reasoning_id},
+                )
+            )
+            self._reasoning_started = False
+
+        if self._text_started:
+            events.append(
+                AiSdkStreamEvent(
+                    AiSdkEventType.TEXT_END,
+                    {"id": self._text_id},
+                )
+            )
+            self._text_started = False
+
+        finish_payload: dict[str, Any] = {}
+        if self._finish_reason is not None:
+            finish_payload["finishReason"] = self._finish_reason.replace("_", "-")
+
+        if self._usage_data is not None:
+            usage_payload: dict[str, Any] = {
+                "promptTokens": self._usage_data.prompt_tokens,
+                "completionTokens": self._usage_data.completion_tokens,
+            }
+            total = getattr(self._usage_data, "total_tokens", None)
+            if total is not None:
+                usage_payload["totalTokens"] = total
+            finish_payload["usage"] = usage_payload
+
+        if finish_payload:
+            events.append(
+                AiSdkStreamEvent(
+                    AiSdkEventType.FINISH,
+                    {"messageMetadata": finish_payload},
+                )
+            )
+        else:
+            events.append(AiSdkStreamEvent(AiSdkEventType.FINISH))
+
+        return events
+
+    def reset_for_next_step(self) -> None:
+        """Reset per-step state between LLM calls in a multi-step flow."""
+        self._tool_calls_state = {}
+        self._finish_reason = None
diff --git a/libs/core/kiln_ai/adapters/model_adapters/test_adapter_stream.py b/libs/core/kiln_ai/adapters/model_adapters/test_adapter_stream.py
new file mode 100644
index 000000000..25715645c
--- /dev/null
+++ b/libs/core/kiln_ai/adapters/model_adapters/test_adapter_stream.py
@@ -0,0 +1,372 @@
+import json
+from typing import Any
+from unittest.mock import AsyncMock, MagicMock, patch
+
+import pytest
+from litellm.types.utils import (
+    ChatCompletionMessageToolCall,
+    Choices,
+    Delta,
+    Function,
+    ModelResponse,
+    ModelResponseStream,
+    StreamingChoices,
+)
+from litellm.types.utils import Message as LiteLLMMessage
+
+from kiln_ai.adapters.chat import ChatFormatter
+from kiln_ai.adapters.model_adapters.adapter_stream import AdapterStream
+from kiln_ai.adapters.model_adapters.stream_events import (
+    ToolCallEvent,
+    ToolCallEventType,
+)
+from kiln_ai.datamodel import Usage
+
+
+def _make_streaming_chunk(
+    content: str | None = None,
+    finish_reason: str | None = None,
+) -> ModelResponseStream:
+    delta = Delta(content=content)
+    choice = StreamingChoices(
+        index=0,
+        delta=delta,
+        finish_reason=finish_reason,
+    )
+    return ModelResponseStream(id="test-stream", choices=[choice])
+
+
+def _make_model_response(
+    content: str = "Hello",
+    tool_calls: list[ChatCompletionMessageToolCall] | None = None,
+) -> ModelResponse:
+    message = LiteLLMMessage(content=content, role="assistant")
+    if tool_calls is not None:
+        message.tool_calls = tool_calls
+    choice = Choices(
+        index=0,
+        message=message,
+        finish_reason="stop" if tool_calls is None else "tool_calls",
+    )
+    return ModelResponse(id="test-response", choices=[choice])
+
+
+def _make_tool_call(
+    call_id: str = "call_1",
+    name: str = "add",
+    arguments: dict[str, Any] | None = None,
+) -> ChatCompletionMessageToolCall:
+    args = json.dumps(arguments or {"a": 1, "b": 2})
+    return ChatCompletionMessageToolCall(
+        id=call_id,
+        type="function",
+        function=Function(name=name, arguments=args),
+    )
+
+
+class FakeChatFormatter(ChatFormatter):
+    """A simple chat formatter that returns a single turn then None."""
+
+    def __init__(self, num_turns: int = 1):
+        self._turn_count = 0
+        self._num_turns = num_turns
+
+    def next_turn(self, prior_output: str | None):
+        if self._turn_count >= self._num_turns:
+            return None
+        self._turn_count += 1
+        turn = MagicMock()
+        turn.messages = [MagicMock(role="user", content="test input")]
+        turn.final_call = self._turn_count == self._num_turns
+        return turn
+
+    def intermediate_outputs(self):
+        return {}
+
+
+class FakeStreamingCompletion:
+    """Mocks StreamingCompletion: yields chunks, then exposes .response"""
+
+    def __init__(
+        self,
+        model_response: ModelResponse,
+        chunks: list[ModelResponseStream] | None = None,
+    ):
+        self._chunks = chunks or [
+            _make_streaming_chunk(content="Hel"),
+            _make_streaming_chunk(content="lo"),
+            _make_streaming_chunk(finish_reason="stop"),
+        ]
+        self._response = model_response
+
+    @property
+    def response(self):
+        return self._response
+
+    async def __aiter__(self):
+        for chunk in self._chunks:
+            yield chunk
+
+
+@pytest.fixture
+def mock_adapter():
+    adapter = MagicMock()
+    adapter.build_completion_kwargs = AsyncMock(return_value={"model": "test"})
+    adapter.usage_from_response = MagicMock(return_value=Usage())
+    adapter.process_tool_calls = AsyncMock(return_value=(None, []))
+    adapter._extract_and_validate_logprobs = MagicMock(return_value=None)
+    adapter._extract_reasoning_to_intermediate_outputs = MagicMock()
+    adapter.all_messages_to_trace = MagicMock(return_value=[])
+    adapter.base_adapter_config = MagicMock()
+    adapter.base_adapter_config.top_logprobs = None
+    return adapter
+
+
+@pytest.fixture
+def mock_provider():
+    provider = MagicMock()
+    provider.model_id = "test-model"
+    return provider
+
+
+class TestAdapterStreamSimple:
+    @pytest.mark.asyncio
+    async def test_simple_content_response(self, mock_adapter, mock_provider):
+        response = _make_model_response(content="Hello world")
+        fake_stream = FakeStreamingCompletion(response)
+        formatter = FakeChatFormatter()
+
+        with patch(
+            "kiln_ai.adapters.model_adapters.adapter_stream.StreamingCompletion",
+            return_value=fake_stream,
+        ):
+            stream = AdapterStream(
+                adapter=mock_adapter,
+                provider=mock_provider,
+                chat_formatter=formatter,
+                initial_messages=[],
+                top_logprobs=None,
+            )
+
+            events = []
+            async for event in stream:
+                events.append(event)
+
+        chunks = [e for e in events if isinstance(e, ModelResponseStream)]
+        assert len(chunks) == 3
+
+        result = stream.result
+        assert result.run_output.output == "Hello world"
+
+    @pytest.mark.asyncio
+    async def test_result_not_available_before_iteration(
+        self, mock_adapter, mock_provider
+    ):
+        stream = AdapterStream(
+            adapter=mock_adapter,
+            provider=mock_provider,
+            chat_formatter=FakeChatFormatter(),
+            initial_messages=[],
+            top_logprobs=None,
+        )
+        with pytest.raises(RuntimeError, match="not been iterated"):
+            _ = stream.result
+
+
+class TestAdapterStreamToolCalls:
+    @pytest.mark.asyncio
+    async def test_tool_call_yields_events(self, mock_adapter, mock_provider):
+        tool_call = _make_tool_call(
+            call_id="call_1", name="add", arguments={"a": 1, "b": 2}
+        )
+        tool_response = _make_model_response(content=None, tool_calls=[tool_call])
+        final_response = _make_model_response(content="The answer is 3")
+
+        tool_stream = FakeStreamingCompletion(
+            tool_response,
+            [_make_streaming_chunk(finish_reason="tool_calls")],
+        )
+        final_stream = FakeStreamingCompletion(
+            final_response,
+            [
+                _make_streaming_chunk(content="The answer is 3"),
+                _make_streaming_chunk(finish_reason="stop"),
+            ],
+        )
+
+        streams_iter = iter([tool_stream, final_stream])
+
+        mock_adapter.process_tool_calls = AsyncMock(
+            return_value=(
+                None,
+                [{"role": "tool", "tool_call_id": "call_1", "content": "3"}],
+            )
+        )
+
+        with patch(
+            "kiln_ai.adapters.model_adapters.adapter_stream.StreamingCompletion",
+            side_effect=lambda **kw: next(streams_iter),
+        ):
+            stream = AdapterStream(
+                adapter=mock_adapter,
+                provider=mock_provider,
+                chat_formatter=FakeChatFormatter(),
+                initial_messages=[],
+                top_logprobs=None,
+            )
+
+            events = []
+            async for event in stream:
+                events.append(event)
+
+        tool_events = [e for e in events if isinstance(e, ToolCallEvent)]
+        assert len(tool_events) == 2
+
+        input_event = next(
+            e for e in tool_events if e.event_type == ToolCallEventType.INPUT_AVAILABLE
+        )
+        assert input_event.tool_call_id == "call_1"
+        assert input_event.tool_name == "add"
+        assert input_event.arguments == {"a": 1, "b": 2}
+
+        output_event = next(
+            e for e in tool_events if e.event_type == ToolCallEventType.OUTPUT_AVAILABLE
+        )
+        assert output_event.tool_call_id == "call_1"
+        assert output_event.result == "3"
+
+        assert stream.result.run_output.output == "The answer is 3"
+
+    @pytest.mark.asyncio
+    async def test_task_response_tool_call(self, mock_adapter, mock_provider):
+        task_response_call = _make_tool_call(
+            call_id="call_tr", name="task_response", arguments={"result": "42"}
+        )
+        response = _make_model_response(content=None, tool_calls=[task_response_call])
+
+        fake_stream = FakeStreamingCompletion(
+            response,
+            [_make_streaming_chunk(finish_reason="tool_calls")],
+        )
+
+        mock_adapter.process_tool_calls = AsyncMock(
+            return_value=('{"result": "42"}', [])
+        )
+
+        with patch(
+            "kiln_ai.adapters.model_adapters.adapter_stream.StreamingCompletion",
+            return_value=fake_stream,
+        ):
+            stream = AdapterStream(
+                adapter=mock_adapter,
+                provider=mock_provider,
+                chat_formatter=FakeChatFormatter(),
+                initial_messages=[],
+                top_logprobs=None,
+            )
+
+            events = []
+            async for event in stream:
+                events.append(event)
+
+        tool_events = [e for e in events if isinstance(e, ToolCallEvent)]
+        assert len(tool_events) == 0
+
+        assert stream.result.run_output.output == '{"result": "42"}'
+
+    @pytest.mark.asyncio
+    async def test_too_many_tool_calls_raises(self, mock_adapter, mock_provider):
+        tool_call = _make_tool_call()
+        response = _make_model_response(content=None, tool_calls=[tool_call])
+
+        mock_adapter.process_tool_calls = AsyncMock(
+            return_value=(
+                None,
+                [{"role": "tool", "tool_call_id": "call_1", "content": "ok"}],
+            )
+        )
+
+        def make_stream(**kw):
+            return FakeStreamingCompletion(
+                response,
+                [_make_streaming_chunk(finish_reason="tool_calls")],
+            )
+
+        with (
+            patch(
+                "kiln_ai.adapters.model_adapters.adapter_stream.StreamingCompletion",
+                side_effect=make_stream,
+            ),
+            patch(
+                "kiln_ai.adapters.model_adapters.adapter_stream.MAX_TOOL_CALLS_PER_TURN",
+                2,
+            ),
+        ):
+            stream = AdapterStream(
+                adapter=mock_adapter,
+                provider=mock_provider,
+                chat_formatter=FakeChatFormatter(),
+                initial_messages=[],
+                top_logprobs=None,
+            )
+
+            with pytest.raises(RuntimeError, match="Too many tool calls"):
+                async for _ in stream:
+                    pass
+
+    @pytest.mark.asyncio
+    async def test_unparseable_tool_call_arguments(self, mock_adapter, mock_provider):
+        bad_tool_call = ChatCompletionMessageToolCall(
+            id="call_bad",
+            type="function",
+            function=Function(name="add", arguments="not json"),
+        )
+        response = _make_model_response(content=None, tool_calls=[bad_tool_call])
+        final_response = _make_model_response(content="fallback")
+
+        tool_stream = FakeStreamingCompletion(
+            response,
+            [_make_streaming_chunk(finish_reason="tool_calls")],
+        )
+        final_stream = FakeStreamingCompletion(
+            final_response,
+            [
+                _make_streaming_chunk(content="fallback"),
+                _make_streaming_chunk(finish_reason="stop"),
+            ],
+        )
+
+        streams_iter = iter([tool_stream, final_stream])
+
+        mock_adapter.process_tool_calls = AsyncMock(
+            return_value=(
+                None,
+                [{"role": "tool", "tool_call_id": "call_bad", "content": "error"}],
+            )
+        )
+
+        with patch(
+            "kiln_ai.adapters.model_adapters.adapter_stream.StreamingCompletion",
+            side_effect=lambda **kw: next(streams_iter),
+        ):
+            stream = AdapterStream(
+                adapter=mock_adapter,
+                provider=mock_provider,
+                chat_formatter=FakeChatFormatter(),
+                initial_messages=[],
+                top_logprobs=None,
+            )
+
+            events = []
+            async for event in stream:
+                events.append(event)
+
+        input_events = [
+            e
+            for e in events
+            if isinstance(e, ToolCallEvent)
+            and e.event_type == ToolCallEventType.INPUT_AVAILABLE
+        ]
+        assert len(input_events) == 1
+        assert input_events[0].arguments is None
+        assert "Failed to parse" in (input_events[0].error or "")
diff --git a/libs/core/kiln_ai/adapters/model_adapters/test_base_adapter.py b/libs/core/kiln_ai/adapters/model_adapters/test_base_adapter.py
index 8b150c68e..b000df81f 100644
--- a/libs/core/kiln_ai/adapters/model_adapters/test_base_adapter.py
+++ b/libs/core/kiln_ai/adapters/model_adapters/test_base_adapter.py
@@ -1,6 +1,13 @@
 from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
+from litellm.types.utils import (
+    ChatCompletionDeltaToolCall,
+    Delta,
+    Function,
+    ModelResponseStream,
+    StreamingChoices,
+)
 
 from kiln_ai.adapters.ml_model_list import KilnModelProvider, StructuredOutputMode
 from kiln_ai.adapters.model_adapters.base_adapter import (
@@ -8,14 +15,13 @@
     BaseAdapter,
     RunOutput,
 )
-from kiln_ai.adapters.prompt_builders import BasePromptBuilder
-from kiln_ai.datamodel import (
-    DataSource,
-    DataSourceType,
-    Task,
-    TaskOutput,
-    TaskRun,
+from kiln_ai.adapters.model_adapters.stream_events import (
+    AiSdkEventType,
+    ToolCallEvent,
+    ToolCallEventType,
 )
+from kiln_ai.adapters.prompt_builders import BasePromptBuilder
+from kiln_ai.datamodel import Task, TaskRun
 from kiln_ai.datamodel.datamodel_enums import ChatStrategy, ModelProviderName
 from kiln_ai.datamodel.project import Project
 from kiln_ai.datamodel.run_config import KilnAgentRunConfigProperties, ToolsRunConfig
@@ -26,7 +32,7 @@
 class MockAdapter(BaseAdapter):
     """Concrete implementation of BaseAdapter for testing"""
 
-    async def _run(self, input, prior_trace=None):
+    async def _run(self, input, **kwargs):
         return None, None
 
     def adapter_name(self) -> str:
@@ -239,7 +245,7 @@ async def test_input_formatting(
         # Mock the _run method to capture the input
         captured_input = None
 
-        async def mock_run(input, prior_trace=None):
+        async def mock_run(input, **kwargs):
             nonlocal captured_input
             captured_input = input
             return RunOutput(output="test output", intermediate_outputs={}), None
@@ -437,7 +443,7 @@ def test_build_chat_formatter_with_prior_trace_returns_multiturn_formatter(adapt
 
 
 @pytest.mark.asyncio
-async def test_existing_run_without_trace_raises(base_project):
+async def test_invoke_with_prior_trace_none_starts_fresh(base_project):
     task = Task(
         name="test_task",
         instruction="test_instruction",
@@ -452,29 +458,44 @@ async def test_existing_run_without_trace_raises(base_project):
             structured_output_mode=StructuredOutputMode.json_schema,
         ),
     )
-    run_without_trace = TaskRun(
-        parent=task,
-        input="hi",
-        input_source=None,
-        output=TaskOutput(
-            output="hello",
-            source=DataSource(
-                type=DataSourceType.synthetic,
-                properties={
-                    "model_name": "gpt_4o",
-                    "model_provider": "openai",
-                    "adapter_name": "test",
-                },
+    adapter._run = AsyncMock(
+        return_value=(
+            RunOutput(output="ok", intermediate_outputs=None, trace=None),
+            None,
+        )
+    )
+    with (
+        patch(
+            "kiln_ai.adapters.model_adapters.base_adapter.model_parser_from_id",
+            return_value=MagicMock(
+                parse_output=MagicMock(
+                    return_value=RunOutput(
+                        output="ok", intermediate_outputs=None, trace=None
+                    )
+                )
             ),
         ),
-        trace=None,
-    )
-    with pytest.raises(ValueError, match="no trace"):
-        await adapter.invoke("input", existing_run=run_without_trace)
+        patch(
+            "kiln_ai.adapters.model_adapters.base_adapter.request_formatter_from_id",
+        ),
+        patch.object(
+            adapter,
+            "model_provider",
+            return_value=MagicMock(
+                parser="default",
+                formatter=None,
+                reasoning_capable=False,
+            ),
+        ),
+    ):
+        run = await adapter.invoke("input", prior_trace=None)
+    assert run.output.output == "ok"
+    adapter._run.assert_called_once()
+    assert adapter._run.call_args[1].get("prior_trace") is None
 
 
 @pytest.mark.asyncio
-async def test_invoke_returning_run_output_passes_existing_run_to_run(
+async def test_invoke_returning_run_output_passes_prior_trace_to_run(
     adapter, mock_parser, tmp_path
 ):
     project = Project(name="proj", path=tmp_path / "proj.kiln")
@@ -491,25 +512,12 @@ async def test_invoke_returning_run_output_passes_existing_run_to_run(
         {"role": "user", "content": "hi"},
         {"role": "assistant", "content": "hello"},
     ]
-    initial_run = adapter.generate_run(
-        input="hi",
-        input_source=None,
-        run_output=RunOutput(
-            output="hello",
-            intermediate_outputs=None,
-            trace=trace,
-        ),
-        trace=trace,
-    )
-    initial_run.save_to_file()
-    run_id = initial_run.id
-    assert run_id is not None
 
     captured_prior_trace = None
 
-    async def mock_run(input, prior_trace=None):
+    async def mock_run(input, **kwargs):
         nonlocal captured_prior_trace
-        captured_prior_trace = prior_trace
+        captured_prior_trace = kwargs.get("prior_trace")
         return RunOutput(output="ok", intermediate_outputs=None, trace=trace), None
 
     adapter._run = mock_run
@@ -532,7 +540,7 @@ async def mock_run(input, prior_trace=None):
             "kiln_ai.adapters.model_adapters.base_adapter.request_formatter_from_id",
         ),
     ):
-        await adapter.invoke_returning_run_output("follow-up", existing_run=initial_run)
+        await adapter.invoke_returning_run_output("follow-up", prior_trace=trace)
 
     assert captured_prior_trace == trace
 
@@ -798,7 +806,7 @@ async def test_invoke_sets_run_context(self, adapter, clear_context):
         from kiln_ai.run_context import get_agent_run_id
 
         # Mock the _run method
-        async def mock_run(input, prior_trace=None):
+        async def mock_run(input, **kwargs):
             # Check that run ID is set during _run
             run_id = get_agent_run_id()
             assert run_id is not None
@@ -838,7 +846,7 @@ async def test_invoke_clears_run_context_after(self, adapter, clear_context):
         from kiln_ai.run_context import get_agent_run_id
 
         # Mock the _run method
-        async def mock_run(input, prior_trace=None):
+        async def mock_run(input, **kwargs):
             return RunOutput(output="test output", intermediate_outputs={}), None
 
         adapter._run = mock_run
@@ -876,7 +884,7 @@ async def test_invoke_clears_run_context_on_error(self, adapter, clear_context):
         from kiln_ai.run_context import get_agent_run_id
 
         # Mock the _run method to raise an error
-        async def mock_run(input, prior_trace=None):
+        async def mock_run(input, **kwargs):
             # Run ID should be set even when error occurs
             run_id = get_agent_run_id()
             assert run_id is not None
@@ -913,7 +921,7 @@ async def test_sub_agent_inherits_run(self, adapter, clear_context):
         set_agent_run_id(parent_run_id)
 
         # Mock the _run method to check inherited run ID
-        async def mock_run(input, prior_trace=None):
+        async def mock_run(input, **kwargs):
             # Sub-agent should see parent's run ID
             run_id = get_agent_run_id()
             assert run_id == parent_run_id
@@ -962,7 +970,7 @@ async def test_sub_agent_does_not_create_new_run(self, adapter, clear_context):
         run_id_during_run = None
 
         # Mock the _run method to capture run ID
-        async def mock_run(input, prior_trace=None):
+        async def mock_run(input, **kwargs):
             nonlocal run_id_during_run
             run_id_during_run = get_agent_run_id()
             return RunOutput(output="test output", intermediate_outputs={}), None
@@ -1002,7 +1010,7 @@ async def test_cleanup_session_called_on_completion(self, adapter, clear_context
         from kiln_ai.adapters.run_output import RunOutput
 
         # Mock the _run method
-        async def mock_run(input, prior_trace=None):
+        async def mock_run(input, **kwargs):
             return RunOutput(output="test output", intermediate_outputs={}), None
 
         adapter._run = mock_run
@@ -1045,3 +1053,185 @@ async def mock_run(input, prior_trace=None):
             assert call_args is not None
             run_id = call_args[0][0] if call_args[0] else call_args[1]["run_id"]
             assert run_id.startswith("run_")
+
+
+class TestStreamMethods:
+    """Tests for the streaming methods on BaseAdapter."""
+
+    @pytest.fixture
+    def stream_adapter(self, base_task):
+        return MockAdapter(
+            task=base_task,
+            run_config=KilnAgentRunConfigProperties(
+                model_name="test_model",
+                model_provider_name="openai",
+                prompt_id="simple_prompt_builder",
+                structured_output_mode="json_schema",
+            ),
+        )
+
+    @pytest.mark.asyncio
+    async def test_invoke_openai_stream_raises_for_unsupported_adapter(
+        self, stream_adapter
+    ):
+        """MockAdapter does not implement _create_run_stream."""
+        provider = MagicMock()
+        provider.formatter = None
+        stream_adapter.model_provider = MagicMock(return_value=provider)
+
+        with pytest.raises(NotImplementedError, match="Streaming is not supported"):
+            async for _chunk in stream_adapter.invoke_openai_stream("test input"):
+                pass
+
+    @pytest.mark.asyncio
+    async def test_invoke_ai_sdk_stream_raises_for_unsupported_adapter(
+        self, stream_adapter
+    ):
+        """MockAdapter does not implement _create_run_stream."""
+        provider = MagicMock()
+        provider.formatter = None
+        stream_adapter.model_provider = MagicMock(return_value=provider)
+
+        with pytest.raises(NotImplementedError, match="Streaming is not supported"):
+            async for _event in stream_adapter.invoke_ai_sdk_stream("test input"):
+                pass
+
+    @pytest.mark.asyncio
+    async def test_invoke_ai_sdk_stream_resets_converter_between_tool_rounds(
+        self, stream_adapter
+    ):
+        """tool-input-start must be emitted for a new tool call at index 0 after a tool round."""
+
+        def _make_tool_chunk(call_id: str, name: str) -> ModelResponseStream:
+            func = Function(name=name, arguments='{"x":1}')
+            tc = ChatCompletionDeltaToolCall(index=0, function=func)
+            tc.id = call_id
+            delta = Delta(tool_calls=[tc])
+            choice = StreamingChoices(index=0, delta=delta, finish_reason=None)
+            return ModelResponseStream(id="test", choices=[choice])
+
+        round1_chunk = _make_tool_chunk("call_r1", "tool_a")
+        round2_chunk = _make_tool_chunk("call_r2", "tool_b")
+
+        fake_events = [
+            round1_chunk,
+            ToolCallEvent(
+                event_type=ToolCallEventType.INPUT_AVAILABLE,
+                tool_call_id="call_r1",
+                tool_name="tool_a",
+                arguments={"x": 1},
+            ),
+            ToolCallEvent(
+                event_type=ToolCallEventType.OUTPUT_AVAILABLE,
+                tool_call_id="call_r1",
+                tool_name="tool_a",
+                result="done",
+            ),
+            round2_chunk,
+        ]
+
+        class FakeAdapterStream:
+            result = MagicMock()
+
+            async def __aiter__(self):
+                for event in fake_events:
+                    yield event
+
+        with (
+            patch.object(
+                stream_adapter,
+                "_prepare_stream",
+                return_value=FakeAdapterStream(),
+            ),
+            patch.object(stream_adapter, "_finalize_stream"),
+        ):
+            events = []
+            async for event in stream_adapter.invoke_ai_sdk_stream("test input"):
+                events.append(event)
+
+        tool_input_starts = [
+            e for e in events if e.type == AiSdkEventType.TOOL_INPUT_START
+        ]
+        assert len(tool_input_starts) == 2, (
+            "tool-input-start must fire once per tool-call round"
+        )
+        assert tool_input_starts[0].payload["toolCallId"] == "call_r1"
+        assert tool_input_starts[1].payload["toolCallId"] == "call_r2"
+
+    @pytest.mark.asyncio
+    async def test_openai_stream_exposes_task_run_after_iteration(self, stream_adapter):
+        fake_chunk = ModelResponseStream(
+            id="test",
+            choices=[
+                StreamingChoices(
+                    index=0,
+                    delta=Delta(content="hi"),
+                    finish_reason=None,
+                )
+            ],
+        )
+
+        class FakeAdapterStream:
+            result = MagicMock()
+
+            async def __aiter__(self):
+                yield fake_chunk
+
+        expected_run = MagicMock(spec=TaskRun)
+
+        with (
+            patch.object(
+                stream_adapter,
+                "_prepare_stream",
+                return_value=FakeAdapterStream(),
+            ),
+            patch.object(stream_adapter, "_finalize_stream", return_value=expected_run),
+        ):
+            stream = stream_adapter.invoke_openai_stream("test input")
+
+            with pytest.raises(RuntimeError, match="not been fully consumed"):
+                _ = stream.task_run
+
+            async for _chunk in stream:
+                pass
+
+            assert stream.task_run is expected_run
+
+    @pytest.mark.asyncio
+    async def test_ai_sdk_stream_exposes_task_run_after_iteration(self, stream_adapter):
+        fake_chunk = ModelResponseStream(
+            id="test",
+            choices=[
+                StreamingChoices(
+                    index=0,
+                    delta=Delta(content="hi"),
+                    finish_reason=None,
+                )
+            ],
+        )
+
+        class FakeAdapterStream:
+            result = MagicMock()
+
+            async def __aiter__(self):
+                yield fake_chunk
+
+        expected_run = MagicMock(spec=TaskRun)
+
+        with (
+            patch.object(
+                stream_adapter,
+                "_prepare_stream",
+                return_value=FakeAdapterStream(),
+            ),
+            patch.object(stream_adapter, "_finalize_stream", return_value=expected_run),
+        ):
+            stream = stream_adapter.invoke_ai_sdk_stream("test input")
+
+            with pytest.raises(RuntimeError, match="not been fully consumed"):
+                _ = stream.task_run
+
+            async for _event in stream:
+                pass
+
+            assert stream.task_run is expected_run
diff --git a/libs/core/kiln_ai/adapters/model_adapters/test_litellm_adapter.py b/libs/core/kiln_ai/adapters/model_adapters/test_litellm_adapter.py
index 3b44812a6..6ec73e6b6 100644
--- a/libs/core/kiln_ai/adapters/model_adapters/test_litellm_adapter.py
+++ b/libs/core/kiln_ai/adapters/model_adapters/test_litellm_adapter.py
@@ -1212,7 +1212,11 @@ async def test_array_input_converted_to_json(tmp_path, config):
     mock_config_obj.user_id = "test_user"
 
     with (
-        patch("litellm.acompletion", new=AsyncMock(return_value=mock_response)),
+        patch.object(
+            LiteLlmAdapter,
+            "acompletion_checking_response",
+            new=AsyncMock(return_value=(mock_response, mock_response.choices[0])),
+        ),
         patch("kiln_ai.utils.config.Config.shared", return_value=mock_config_obj),
     ):
         array_input = [1, 2, 3, 4, 5]
@@ -1282,7 +1286,11 @@ async def test_dict_input_converted_to_json(tmp_path, config):
     mock_config_obj.user_id = "test_user"
 
     with (
-        patch("litellm.acompletion", new=AsyncMock(return_value=mock_response)),
+        patch.object(
+            LiteLlmAdapter,
+            "acompletion_checking_response",
+            new=AsyncMock(return_value=(mock_response, mock_response.choices[0])),
+        ),
         patch("kiln_ai.utils.config.Config.shared", return_value=mock_config_obj),
     ):
         dict_input = {"x": 10, "y": 20}
@@ -1362,3 +1370,121 @@ async def mock_run_model_turn(
     assert run_output.trace[1]["content"] == "hello"
     assert run_output.trace[2]["content"] == "follow-up"
     assert run_output.trace[3]["content"] == "How can I help?"
+
+
+@pytest.mark.asyncio
+async def test_run_with_prior_trace_preserves_tool_calls(mock_task):
+    """Prior trace containing tool calls should be passed through to the model and preserved in the output trace."""
+    config = LiteLlmConfig(
+        base_url="https://api.test.com",
+        run_config_properties=KilnAgentRunConfigProperties(
+            model_name="test-model",
+            model_provider_name="openai_compatible",
+            prompt_id="simple_prompt_builder",
+            structured_output_mode="json_schema",
+        ),
+        default_headers={"X-Test": "test"},
+        additional_body_options={"api_key": "test_key"},
+    )
+
+    prior_trace = [
+        {"role": "system", "content": "Use the math tools."},
+        {"role": "user", "content": "4"},
+        {
+            "role": "assistant",
+            "content": "",
+            "reasoning_content": "Let me multiply 4 by 7.\n",
+            "tool_calls": [
+                {
+                    "id": "call_abc123",
+                    "function": {"arguments": '{"a": 4, "b": 7}', "name": "multiply"},
+                    "type": "function",
+                }
+            ],
+        },
+        {
+            "content": "28",
+            "role": "tool",
+            "tool_call_id": "call_abc123",
+            "kiln_task_tool_data": None,
+        },
+        {
+            "role": "assistant",
+            "content": "",
+            "reasoning_content": "Now add 144.\n",
+            "tool_calls": [
+                {
+                    "id": "call_def456",
+                    "function": {"arguments": '{"a": 28, "b": 144}', "name": "add"},
+                    "type": "function",
+                }
+            ],
+        },
+        {
+            "content": "172",
+            "role": "tool",
+            "tool_call_id": "call_def456",
+            "kiln_task_tool_data": None,
+        },
+        {
+            "role": "assistant",
+            "content": "There were 172 distinct species of giant tortoises.",
+            "reasoning_content": "Now I have 172.\n",
+        },
+    ]
+    adapter = LiteLlmAdapter(config=config, kiln_task=mock_task)
+
+    captured_messages = []
+
+    async def mock_run_model_turn(
+        provider, prior_messages, top_logprobs, skip_response_format
+    ):
+        captured_messages.extend(prior_messages)
+        extended = list(prior_messages)
+        extended.append({"role": "assistant", "content": '{"test": "response"}'})
+        return ModelTurnResult(
+            assistant_message='{"test": "response"}',
+            all_messages=extended,
+            model_response=None,
+            model_choice=None,
+            usage=Usage(),
+        )
+
+    adapter._run_model_turn = mock_run_model_turn
+
+    run_output, _ = await adapter._run("what else?", prior_trace=prior_trace)
+
+    assert run_output.trace is not None
+    # 7 prior trace messages + 1 new user + 1 new assistant = 9
+    assert len(run_output.trace) == 9
+
+    # Verify tool call messages are preserved in the trace
+    assistant_with_tools = run_output.trace[2]
+    assert assistant_with_tools["role"] == "assistant"
+    assert assistant_with_tools["tool_calls"][0]["id"] == "call_abc123"
+    assert assistant_with_tools["tool_calls"][0]["function"]["name"] == "multiply"
+    assert assistant_with_tools["reasoning_content"] == "Let me multiply 4 by 7.\n"
+
+    tool_response = run_output.trace[3]
+    assert tool_response["role"] == "tool"
+    assert tool_response["tool_call_id"] == "call_abc123"
+    assert tool_response["content"] == "28"
+
+    second_tool_call = run_output.trace[4]
+    assert second_tool_call["tool_calls"][0]["id"] == "call_def456"
+    assert second_tool_call["tool_calls"][0]["function"]["name"] == "add"
+
+    second_tool_response = run_output.trace[5]
+    assert second_tool_response["role"] == "tool"
+    assert second_tool_response["tool_call_id"] == "call_def456"
+    assert second_tool_response["content"] == "172"
+
+    # Verify the tool call messages were passed to _run_model_turn (i.e., sent to the model)
+    assert any(
+        m.get("tool_calls") is not None
+        for m in captured_messages
+        if isinstance(m, dict)
+    )
+    assert any(
+        m.get("role") == "tool" for m in captured_messages if isinstance(m, dict)
+    )
diff --git a/libs/core/kiln_ai/adapters/model_adapters/test_litellm_adapter_streaming.py b/libs/core/kiln_ai/adapters/model_adapters/test_litellm_adapter_streaming.py
new file mode 100644
index 000000000..65c540376
--- /dev/null
+++ b/libs/core/kiln_ai/adapters/model_adapters/test_litellm_adapter_streaming.py
@@ -0,0 +1,308 @@
+import json
+import logging
+import re
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import Any, Callable
+
+import litellm
+import pytest
+from litellm.types.utils import ChatCompletionDeltaToolCall
+
+from kiln_ai.adapters.ml_model_list import ModelProviderName, StructuredOutputMode
+from kiln_ai.adapters.model_adapters.litellm_adapter import LiteLlmAdapter
+from kiln_ai.adapters.model_adapters.litellm_config import LiteLlmConfig
+from kiln_ai.adapters.model_adapters.stream_events import (
+    AiSdkEventType,
+    AiSdkStreamEvent,
+)
+from kiln_ai.datamodel import Project, PromptGenerators, Task
+from kiln_ai.datamodel.run_config import KilnAgentRunConfigProperties, ToolsRunConfig
+from kiln_ai.datamodel.tool_id import KilnBuiltInToolId
+
+logger = logging.getLogger(__name__)
+
+STREAMING_MODELS = [
+    ("claude_sonnet_4_5", ModelProviderName.openrouter),
+    ("claude_sonnet_4_5", ModelProviderName.anthropic),
+    ("claude_sonnet_4_6", ModelProviderName.openrouter),
+    ("claude_sonnet_4_6", ModelProviderName.anthropic),
+    ("claude_opus_4_5", ModelProviderName.openrouter),
+    ("claude_opus_4_5", ModelProviderName.anthropic),
+    ("claude_opus_4_6", ModelProviderName.openrouter),
+    ("claude_opus_4_6", ModelProviderName.anthropic),
+    ("minimax_m2_5", ModelProviderName.openrouter),
+    ("claude_4_5_haiku", ModelProviderName.openrouter),
+    ("claude_4_5_haiku", ModelProviderName.anthropic),
+]
+
+STREAMING_MODELS_NO_HAIKU = [m for m in STREAMING_MODELS if "haiku" not in m[0]]
+
+PAID_TEST_OUTPUT_DIR = Path(__file__).resolve().parents[5] / "test_output"
+
+
+def _serialize_for_dump(obj: Any) -> Any:
+    if hasattr(obj, "model_dump"):
+        return obj.model_dump(mode="json")
+    if isinstance(obj, list):
+        if not obj:
+            return []
+        first = obj[0]
+        if hasattr(first, "type") and hasattr(first, "payload"):
+            return [{"type": e.type.value, "payload": e.payload} for e in obj]
+        if hasattr(first, "model_dump"):
+            return [item.model_dump(mode="json") for item in obj]
+        return [_serialize_for_dump(x) for x in obj]
+    return obj
+
+
+def _dump_paid_test_output(request: pytest.FixtureRequest, **payloads: Any) -> Path:
+    test_name = re.sub(r"[^\w\-]", "_", request.node.name)
+    param_id = "default"
+    if hasattr(request.node, "callspec") and request.node.callspec is not None:
+        id_attr = getattr(request.node.callspec, "id", None)
+        if id_attr is not None:
+            param_id = re.sub(r"[^\w\-]", "_", str(id_attr))
+    timestamp = datetime.now(timezone.utc).strftime("%Y-%m-%dT%H-%M-%S")
+    out_dir = PAID_TEST_OUTPUT_DIR / test_name / param_id / timestamp
+    out_dir.mkdir(parents=True, exist_ok=True)
+    for filename, data in payloads.items():
+        if data is None:
+            continue
+        if not filename.endswith(".json"):
+            filename = f"{filename}.json"
+        serialized = _serialize_for_dump(data)
+        (out_dir / filename).write_text(
+            json.dumps(serialized, indent=2, default=str), encoding="utf-8"
+        )
+    return out_dir
+
+
+@pytest.fixture
+def task(tmp_path):
+    project_path: Path = tmp_path / "test_project" / "project.kiln"
+    project_path.parent.mkdir()
+
+    project = Project(name="Test Project", path=project_path)
+    project.save_to_file()
+
+    task = Task(
+        name="Streaming Test Task",
+        instruction="Think about it hard! Solve the math problem provided by the user, in a step by step manner. Use the tools provided to solve the math problem. Then use the result in a short sentence about a cat going to the mall. Remember to use the tools for math even if the operation looks easy.",
+        parent=project,
+    )
+    task.save_to_file()
+    return task
+
+
+@pytest.fixture
+def adapter_factory(task: Task) -> Callable[[str, ModelProviderName], LiteLlmAdapter]:
+    def create_adapter(
+        model_id: str, provider_name: ModelProviderName
+    ) -> LiteLlmAdapter:
+        return LiteLlmAdapter(
+            kiln_task=task,
+            config=LiteLlmConfig(
+                run_config_properties=KilnAgentRunConfigProperties(
+                    model_name=model_id,
+                    model_provider_name=provider_name,
+                    prompt_id=PromptGenerators.SIMPLE,
+                    structured_output_mode=StructuredOutputMode.unknown,
+                    tools_config=ToolsRunConfig(
+                        tools=[
+                            KilnBuiltInToolId.ADD_NUMBERS,
+                            KilnBuiltInToolId.SUBTRACT_NUMBERS,
+                            KilnBuiltInToolId.MULTIPLY_NUMBERS,
+                            KilnBuiltInToolId.DIVIDE_NUMBERS,
+                        ],
+                    ),
+                )
+            ),
+        )
+
+    return create_adapter
+
+
+@pytest.mark.paid
+@pytest.mark.parametrize("model_id,provider_name", STREAMING_MODELS)
+async def test_invoke_openai_stream_chunks(
+    request: pytest.FixtureRequest,
+    model_id: str,
+    provider_name: ModelProviderName,
+    adapter_factory: Callable[[str, ModelProviderName], LiteLlmAdapter],
+):
+    """Collect all OpenAI-protocol chunks via invoke_openai_stream and verify we got reasoning, content, and tool call data."""
+    adapter = adapter_factory(model_id, provider_name)
+
+    chunks: list[litellm.ModelResponseStream] = []
+    async for chunk in adapter.invoke_openai_stream(input="123 + 321 = ?"):
+        chunks.append(chunk)
+
+    _dump_paid_test_output(request, chunks=chunks)
+    assert len(chunks) > 0, "No chunks collected"
+
+    reasoning_contents: list[str] = []
+    contents: list[str] = []
+    tool_calls: list[ChatCompletionDeltaToolCall | Any] = []
+
+    for chunk in chunks:
+        if chunk.choices[0].finish_reason is not None:
+            continue
+        delta = chunk.choices[0].delta
+        if delta is None:
+            continue
+        if delta.tool_calls is not None:
+            tool_calls.extend(delta.tool_calls)
+        elif getattr(delta, "reasoning_content", None) is not None:
+            text = getattr(delta, "reasoning_content", None)
+            if text is not None:
+                reasoning_contents.append(text)
+        elif delta.content is not None:
+            contents.append(delta.content)
+
+    assert len(reasoning_contents) > 0, "No reasoning content in chunks"
+    assert len(contents) > 0, "No content in chunks"
+    assert len(tool_calls) > 0, "No tool calls in chunks"
+    assert not all(r.strip() == "" for r in reasoning_contents), (
+        "All reasoning content in chunks is empty"
+    )
+    assert not all(c.strip() == "" for c in contents), "All content in chunks is empty"
+
+    tool_call_function_names = [
+        tc.function.name for tc in tool_calls if tc.function.name is not None
+    ]
+    assert len(tool_call_function_names) == 1, (
+        "Expected exactly one tool call function name"
+    )
+    assert tool_call_function_names[0] == "add", "Tool call function name is not 'add'"
+
+    tool_call_args_chunks = "".join(
+        tc.function.arguments for tc in tool_calls if tc.function.arguments is not None
+    )
+    tool_call_args = json.loads(tool_call_args_chunks)
+    assert tool_call_args == {"a": 123, "b": 321} or tool_call_args == {
+        "a": 321,
+        "b": 123,
+    }, f"Tool call arguments not as expected: {tool_call_args}"
+
+
+@pytest.mark.paid
+@pytest.mark.parametrize("model_id,provider_name", STREAMING_MODELS)
+async def test_invoke_ai_sdk_stream(
+    request: pytest.FixtureRequest,
+    model_id: str,
+    provider_name: ModelProviderName,
+    adapter_factory: Callable[[str, ModelProviderName], LiteLlmAdapter],
+):
+    """Collect AI SDK events and verify the full protocol lifecycle including tool events."""
+    adapter = adapter_factory(model_id, provider_name)
+
+    events: list[AiSdkStreamEvent] = []
+    async for event in adapter.invoke_ai_sdk_stream(input="123 + 321 = ?"):
+        events.append(event)
+        logger.info(f"AI SDK event: {event.type.value} {event.payload}")
+
+    _dump_paid_test_output(request, events=events)
+    assert len(events) > 0, "No events collected"
+
+    event_types = [e.type for e in events]
+
+    assert event_types[0] == AiSdkEventType.START, "First event should be START"
+    assert event_types[1] == AiSdkEventType.START_STEP, (
+        "Second event should be START_STEP"
+    )
+
+    assert AiSdkEventType.FINISH_STEP in event_types, "Should have FINISH_STEP"
+    assert AiSdkEventType.FINISH in event_types, "Should have FINISH"
+
+    assert AiSdkEventType.REASONING_START in event_types, "Should have REASONING_START"
+    assert AiSdkEventType.REASONING_DELTA in event_types, "Should have REASONING_DELTA"
+
+    assert AiSdkEventType.TEXT_START in event_types, "Should have TEXT_START"
+    assert AiSdkEventType.TEXT_DELTA in event_types, "Should have TEXT_DELTA"
+    assert AiSdkEventType.TEXT_END in event_types, "Should have TEXT_END"
+
+    assert AiSdkEventType.TOOL_INPUT_START in event_types, (
+        "Should have TOOL_INPUT_START"
+    )
+    assert AiSdkEventType.TOOL_INPUT_AVAILABLE in event_types, (
+        "Should have TOOL_INPUT_AVAILABLE"
+    )
+    assert AiSdkEventType.TOOL_OUTPUT_AVAILABLE in event_types, (
+        "Should have TOOL_OUTPUT_AVAILABLE"
+    )
+
+    text_deltas = [
+        e.payload.get("delta", "")
+        for e in events
+        if e.type == AiSdkEventType.TEXT_DELTA
+    ]
+    full_text = "".join(text_deltas)
+    assert len(full_text) > 0, "Text content is empty"
+
+    tool_input_available = [
+        e for e in events if e.type == AiSdkEventType.TOOL_INPUT_AVAILABLE
+    ]
+    assert len(tool_input_available) >= 1, (
+        "Should have at least one tool-input-available"
+    )
+    tool_input = tool_input_available[0].payload.get("input", {})
+    assert "a" in tool_input and "b" in tool_input, (
+        f"Tool input should have a and b keys: {tool_input}"
+    )
+
+    tool_output_available = [
+        e for e in events if e.type == AiSdkEventType.TOOL_OUTPUT_AVAILABLE
+    ]
+    assert len(tool_output_available) >= 1, (
+        "Should have at least one tool-output-available"
+    )
+    assert tool_output_available[0].payload.get("output") is not None, (
+        "Tool output should not be None"
+    )
+
+
+@pytest.mark.paid
+@pytest.mark.parametrize("model_id,provider_name", STREAMING_MODELS_NO_HAIKU)
+async def test_invoke_openai_stream_non_streaming_still_works(
+    request: pytest.FixtureRequest,
+    model_id: str,
+    provider_name: ModelProviderName,
+    adapter_factory: Callable[[str, ModelProviderName], LiteLlmAdapter],
+):
+    """Verify the non-streaming invoke() still works after the refactor."""
+    adapter = adapter_factory(model_id, provider_name)
+    task_run = await adapter.invoke(input="123 + 321 = ?")
+
+    _dump_paid_test_output(request, task_run=task_run)
+    assert task_run.trace is not None, "Task run trace is None"
+    assert len(task_run.trace) > 0, "Task run trace is empty"
+    assert "444" in task_run.output.output, (
+        f"Expected 444 in output: {task_run.output.output}"
+    )
+
+
+@pytest.mark.paid
+@pytest.mark.parametrize("model_id,provider_name", STREAMING_MODELS_NO_HAIKU)
+async def test_invoke_openai_stream_with_prior_trace(
+    request: pytest.FixtureRequest,
+    model_id: str,
+    provider_name: ModelProviderName,
+    adapter_factory: Callable[[str, ModelProviderName], LiteLlmAdapter],
+):
+    """Test that streaming works when continuing an existing run (session continuation)."""
+    adapter = adapter_factory(model_id, provider_name)
+
+    initial_run = await adapter.invoke(input="123 + 321 = ?")
+    assert initial_run.trace is not None
+    assert len(initial_run.trace) > 0
+
+    continuation_chunks: list[litellm.ModelResponseStream] = []
+    async for chunk in adapter.invoke_openai_stream(
+        input="What was the result? Reply in one short sentence.",
+        prior_trace=initial_run.trace,
+    ):
+        continuation_chunks.append(chunk)
+
+    _dump_paid_test_output(request, continuation_chunks=continuation_chunks)
+    assert len(continuation_chunks) > 0, "No continuation chunks collected"
diff --git a/libs/core/kiln_ai/adapters/model_adapters/test_litellm_adapter_tools.py b/libs/core/kiln_ai/adapters/model_adapters/test_litellm_adapter_tools.py
index fb7bc4c21..3674fe5b3 100644
--- a/libs/core/kiln_ai/adapters/model_adapters/test_litellm_adapter_tools.py
+++ b/libs/core/kiln_ai/adapters/model_adapters/test_litellm_adapter_tools.py
@@ -1,6 +1,6 @@
 import json
 from pathlib import Path
-from unittest.mock import Mock, patch
+from unittest.mock import AsyncMock, Mock, patch
 
 import pytest
 from litellm.types.utils import ModelResponse
@@ -287,10 +287,17 @@ async def test_tools_simplied_mocked(tmp_path):
     mock_config.open_ai_api_key = "mock_api_key"
     mock_config.user_id = "test_user"
 
+    responses = [mock_response_1, mock_response_2]
+
+    async def mock_acompletion_checking_response(self, **kwargs):
+        response = responses.pop(0)
+        return response, response.choices[0]
+
     with (
-        patch(
-            "litellm.acompletion",
-            side_effect=[mock_response_1, mock_response_2],
+        patch.object(
+            LiteLlmAdapter,
+            "acompletion_checking_response",
+            new=mock_acompletion_checking_response,
         ),
         patch("kiln_ai.utils.config.Config.shared", return_value=mock_config),
     ):
@@ -386,9 +393,16 @@ async def test_tools_mocked(tmp_path):
     mock_config.user_id = "test_user"
 
     with (
-        patch(
-            "litellm.acompletion",
-            side_effect=[mock_response_1, mock_response_2, mock_response_3],
+        patch.object(
+            LiteLlmAdapter,
+            "acompletion_checking_response",
+            new=AsyncMock(
+                side_effect=[
+                    (mock_response_1, mock_response_1.choices[0]),
+                    (mock_response_2, mock_response_2.choices[0]),
+                    (mock_response_3, mock_response_3.choices[0]),
+                ]
+            ),
         ),
         patch("kiln_ai.utils.config.Config.shared", return_value=mock_config),
     ):
diff --git a/libs/core/kiln_ai/adapters/model_adapters/test_mcp_adapter.py b/libs/core/kiln_ai/adapters/model_adapters/test_mcp_adapter.py
index ad5826d8c..cb0a3e94b 100644
--- a/libs/core/kiln_ai/adapters/model_adapters/test_mcp_adapter.py
+++ b/libs/core/kiln_ai/adapters/model_adapters/test_mcp_adapter.py
@@ -334,7 +334,7 @@ async def test_mcp_adapter_sets_and_clears_run_context(
 async def test_mcp_adapter_rejects_multiturn_invoke_returning_run_output(
     project_with_local_mcp_server, local_mcp_tool_id
 ):
-    """Session continuation (existing_run) is not supported for MCP adapter."""
+    """Session continuation (prior_trace) is not supported for MCP adapter."""
     project, _ = project_with_local_mcp_server
     task = Task(
         name="Test Task",
@@ -352,7 +352,9 @@ async def test_mcp_adapter_rejects_multiturn_invoke_returning_run_output(
     existing_run.trace = [{"role": "user", "content": "hi"}]
 
     with pytest.raises(NotImplementedError) as exc_info:
-        await adapter.invoke_returning_run_output("input", existing_run=existing_run)
+        await adapter.invoke_returning_run_output(
+            "input", prior_trace=existing_run.trace
+        )
 
     assert "Session continuation is not supported" in str(exc_info.value)
     assert "MCP adapter" in str(exc_info.value)
@@ -362,7 +364,7 @@ async def test_mcp_adapter_rejects_multiturn_invoke_returning_run_output(
 async def test_mcp_adapter_rejects_multiturn_invoke(
     project_with_local_mcp_server, local_mcp_tool_id
 ):
-    """invoke with existing_run raises NotImplementedError for MCP adapter."""
+    """invoke with prior_trace raises NotImplementedError for MCP adapter."""
     project, _ = project_with_local_mcp_server
     task = Task(
         name="Test Task",
@@ -380,7 +382,7 @@ async def test_mcp_adapter_rejects_multiturn_invoke(
     existing_run.trace = [{"role": "user", "content": "hi"}]
 
     with pytest.raises(NotImplementedError) as exc_info:
-        await adapter.invoke("input", existing_run=existing_run)
+        await adapter.invoke("input", prior_trace=existing_run.trace)
 
     assert "Session continuation is not supported" in str(exc_info.value)
 
diff --git a/libs/core/kiln_ai/adapters/model_adapters/test_saving_adapter_results.py b/libs/core/kiln_ai/adapters/model_adapters/test_saving_adapter_results.py
index f96c70a41..db20fe5ea 100644
--- a/libs/core/kiln_ai/adapters/model_adapters/test_saving_adapter_results.py
+++ b/libs/core/kiln_ai/adapters/model_adapters/test_saving_adapter_results.py
@@ -1,4 +1,4 @@
-from unittest.mock import MagicMock, patch
+from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
 
@@ -10,11 +10,7 @@
 
 
 class MockAdapter(BaseAdapter):
-    async def _run(
-        self,
-        input: InputType,
-        prior_trace=None,
-    ) -> tuple[RunOutput, Usage | None]:
+    async def _run(self, input: InputType, **kwargs) -> tuple[RunOutput, Usage | None]:
         return RunOutput(output="Test output", intermediate_outputs=None), None
 
     def adapter_name(self) -> str:
@@ -239,7 +235,7 @@ async def test_autosave_true(test_task, adapter):
 
 @pytest.mark.asyncio
 async def test_invoke_continue_session(test_task, adapter):
-    """Test that invoke with task_run_id continues a session and updates the run."""
+    """Test that invoke with prior_trace continues a session and creates a new run."""
     with patch("kiln_ai.utils.config.Config.shared") as mock_shared:
         mock_config = mock_shared.return_value
         mock_config.autosave_runs = True
@@ -249,21 +245,9 @@ async def test_invoke_continue_session(test_task, adapter):
             {"role": "user", "content": "Hello"},
             {"role": "assistant", "content": "Hi there!"},
         ]
-        initial_run = adapter.generate_run(
-            input="Hello",
-            input_source=None,
-            run_output=RunOutput(
-                output="Hi there!",
-                intermediate_outputs=None,
-                trace=trace,
-            ),
-            trace=trace,
-        )
-        initial_run.save_to_file()
-        run_id = initial_run.id
-        assert run_id is not None
 
-        async def mock_run(input, prior_trace=None):
+        async def mock_run(input, **kwargs):
+            prior_trace = kwargs.get("prior_trace")
             if prior_trace is not None:
                 extended_trace = [
                     *prior_trace,
@@ -309,14 +293,14 @@ async def mock_run(input, prior_trace=None):
             )
             mock_parser_from_id.return_value = mock_parser
 
-            updated_run = await adapter.invoke("Tell me more", existing_run=initial_run)
+            new_run = await adapter.invoke("Tell me more", prior_trace=trace)
 
-        assert updated_run.id == run_id
-        assert updated_run.input == "Hello"
-        assert updated_run.output.output == "How can I help?"
-        assert len(updated_run.trace) == 4
-        assert updated_run.trace[-2]["content"] == "Tell me more"
-        assert updated_run.trace[-1]["content"] == "How can I help?"
+        assert new_run.id is not None
+        assert new_run.input == "Tell me more"
+        assert new_run.output.output == "How can I help?"
+        assert len(new_run.trace) == 4
+        assert new_run.trace[-2]["content"] == "Tell me more"
+        assert new_run.trace[-1]["content"] == "How can I help?"
 
         reloaded = Task.load_from_file(test_task.path)
         runs = reloaded.runs()
@@ -325,36 +309,55 @@ async def mock_run(input, prior_trace=None):
 
 
 @pytest.mark.asyncio
-async def test_invoke_continue_run_without_trace(test_task, adapter):
-    """Test that invoke with existing_run that has no trace raises ValueError."""
+async def test_invoke_with_empty_prior_trace_starts_fresh(test_task, adapter):
+    """Test that invoke with prior_trace=[] starts a fresh conversation (no error)."""
     with patch("kiln_ai.utils.config.Config.shared") as mock_shared:
         mock_config = mock_shared.return_value
         mock_config.autosave_runs = True
         mock_config.user_id = "test_user"
 
-        run_without_trace = adapter.generate_run(
-            input="Hello",
-            input_source=None,
-            run_output=RunOutput(
-                output="Hi",
-                intermediate_outputs=None,
-                trace=None,
-            ),
+        adapter._run = AsyncMock(
+            return_value=(
+                RunOutput(output="Fresh reply", intermediate_outputs=None, trace=None),
+                None,
+            )
         )
-        run_without_trace.save_to_file()
-
-        with pytest.raises(ValueError, match="no trace"):
-            await adapter.invoke("Follow up", existing_run=run_without_trace)
+        with (
+            patch.object(
+                adapter,
+                "model_provider",
+                return_value=MagicMock(
+                    parser="default",
+                    formatter=None,
+                    reasoning_capable=False,
+                ),
+            ),
+            patch(
+                "kiln_ai.adapters.model_adapters.base_adapter.model_parser_from_id",
+                return_value=MagicMock(
+                    parse_output=MagicMock(
+                        return_value=RunOutput(
+                            output="Fresh reply",
+                            intermediate_outputs=None,
+                            trace=None,
+                        )
+                    )
+                ),
+            ),
+            patch(
+                "kiln_ai.adapters.model_adapters.base_adapter.request_formatter_from_id",
+            ),
+        ):
+            run = await adapter.invoke("Follow up", prior_trace=[])
+        assert run.output.output == "Fresh reply"
 
 
-def test_generate_run_with_existing_run_merges_usage_and_intermediate_outputs(
-    test_task, adapter
-):
+def test_generate_run_always_creates_new_task_run(test_task, adapter):
     trace = [
         {"role": "user", "content": "hi"},
         {"role": "assistant", "content": "hello"},
     ]
-    initial_run = adapter.generate_run(
+    run1 = adapter.generate_run(
         input="hi",
         input_source=None,
         run_output=RunOutput(
@@ -370,8 +373,8 @@ def test_generate_run_with_existing_run_merges_usage_and_intermediate_outputs(
         {"role": "user", "content": "follow-up"},
         {"role": "assistant", "content": "ok"},
     ]
-    result = adapter.generate_run(
-        input="hi",
+    run2 = adapter.generate_run(
+        input="follow-up",
         input_source=None,
         run_output=RunOutput(
             output="ok",
@@ -380,16 +383,12 @@ def test_generate_run_with_existing_run_merges_usage_and_intermediate_outputs(
         ),
         usage=Usage(input_tokens=5, output_tokens=10),
         trace=extended_trace,
-        existing_run=initial_run,
     )
-    assert result is initial_run
-    assert result.usage.input_tokens == 15
-    assert result.usage.output_tokens == 30
-    assert result.intermediate_outputs == {
-        "chain_of_thought": "old",
-        "new_key": "new_val",
-    }
-    assert result.output.output == "ok"
+    assert run2 is not run1
+    assert run2.usage is not None and run2.usage.input_tokens == 5
+    assert run2.usage.output_tokens == 10
+    assert run2.intermediate_outputs == {"new_key": "new_val"}
+    assert run2.output.output == "ok"
 
 
 def test_properties_for_task_output_custom_values(test_task):
diff --git a/libs/core/kiln_ai/adapters/model_adapters/test_stream_events.py b/libs/core/kiln_ai/adapters/model_adapters/test_stream_events.py
new file mode 100644
index 000000000..d4f3b3e43
--- /dev/null
+++ b/libs/core/kiln_ai/adapters/model_adapters/test_stream_events.py
@@ -0,0 +1,267 @@
+from litellm.types.utils import (
+    ChatCompletionDeltaToolCall,
+    Delta,
+    Function,
+    ModelResponseStream,
+    StreamingChoices,
+)
+
+from kiln_ai.adapters.model_adapters.stream_events import (
+    AiSdkEventType,
+    AiSdkStreamConverter,
+    AiSdkStreamEvent,
+    ToolCallEvent,
+    ToolCallEventType,
+)
+
+
+def _make_tool_call_delta(
+    index: int = 0,
+    call_id: str | None = None,
+    name: str | None = None,
+    arguments: str | None = None,
+) -> ChatCompletionDeltaToolCall:
+    func = Function(name=name, arguments=arguments or "")
+    tc = ChatCompletionDeltaToolCall(index=index, function=func)
+    if call_id is not None:
+        tc.id = call_id
+    return tc
+
+
+def _make_chunk(
+    content: str | None = None,
+    reasoning_content: str | None = None,
+    tool_calls: list[ChatCompletionDeltaToolCall] | None = None,
+    finish_reason: str | None = None,
+) -> ModelResponseStream:
+    delta = Delta(content=content, tool_calls=tool_calls)
+    if reasoning_content is not None:
+        delta.reasoning_content = reasoning_content
+    choice = StreamingChoices(
+        index=0,
+        delta=delta,
+        finish_reason=finish_reason,
+    )
+    return ModelResponseStream(id="test", choices=[choice])
+
+
+class TestAiSdkStreamEvent:
+    def test_model_dump(self):
+        event = AiSdkStreamEvent(AiSdkEventType.START, {"messageId": "msg-123"})
+        dump = event.model_dump()
+        assert dump["type"] == "start"
+        assert dump["messageId"] == "msg-123"
+
+
+class TestAiSdkStreamConverter:
+    def test_text_start_and_delta(self):
+        converter = AiSdkStreamConverter()
+        events = converter.convert_chunk(_make_chunk(content="Hello"))
+        types = [e.type for e in events]
+        assert AiSdkEventType.TEXT_START in types
+        assert AiSdkEventType.TEXT_DELTA in types
+        assert events[-1].payload["delta"] == "Hello"
+
+    def test_text_delta_no_duplicate_start(self):
+        converter = AiSdkStreamConverter()
+        converter.convert_chunk(_make_chunk(content="Hello"))
+        events = converter.convert_chunk(_make_chunk(content=" world"))
+        types = [e.type for e in events]
+        assert AiSdkEventType.TEXT_START not in types
+        assert AiSdkEventType.TEXT_DELTA in types
+
+    def test_reasoning_start_and_delta(self):
+        converter = AiSdkStreamConverter()
+        events = converter.convert_chunk(_make_chunk(reasoning_content="Thinking..."))
+        types = [e.type for e in events]
+        assert AiSdkEventType.REASONING_START in types
+        assert AiSdkEventType.REASONING_DELTA in types
+
+    def test_reasoning_ends_when_content_starts(self):
+        converter = AiSdkStreamConverter()
+        converter.convert_chunk(_make_chunk(reasoning_content="Thinking..."))
+        events = converter.convert_chunk(_make_chunk(content="Answer"))
+        types = [e.type for e in events]
+        assert AiSdkEventType.REASONING_END in types
+        assert AiSdkEventType.TEXT_START in types
+
+    def test_reasoning_ends_when_tool_calls_start(self):
+        converter = AiSdkStreamConverter()
+        converter.convert_chunk(_make_chunk(reasoning_content="Thinking..."))
+
+        tc_delta = _make_tool_call_delta(
+            index=0, call_id="call_1", name="add", arguments='{"a":1}'
+        )
+        events = converter.convert_chunk(_make_chunk(tool_calls=[tc_delta]))
+        types = [e.type for e in events]
+        assert AiSdkEventType.REASONING_END in types
+
+    def test_tool_call_input_start_and_delta(self):
+        converter = AiSdkStreamConverter()
+
+        tc_delta = _make_tool_call_delta(
+            index=0, call_id="call_1", name="add", arguments='{"a":'
+        )
+        events = converter.convert_chunk(_make_chunk(tool_calls=[tc_delta]))
+        types = [e.type for e in events]
+        assert AiSdkEventType.TOOL_INPUT_START in types
+        assert AiSdkEventType.TOOL_INPUT_DELTA in types
+
+        start_event = next(
+            e for e in events if e.type == AiSdkEventType.TOOL_INPUT_START
+        )
+        assert start_event.payload["toolCallId"] == "call_1"
+        assert start_event.payload["toolName"] == "add"
+
+    def test_finalize_closes_open_blocks(self):
+        converter = AiSdkStreamConverter()
+        converter.convert_chunk(_make_chunk(content="text"))
+        events = converter.finalize()
+        types = [e.type for e in events]
+        assert AiSdkEventType.TEXT_END in types
+        assert AiSdkEventType.FINISH in types
+
+    def test_finalize_closes_reasoning(self):
+        converter = AiSdkStreamConverter()
+        converter.convert_chunk(_make_chunk(reasoning_content="thinking"))
+        events = converter.finalize()
+        types = [e.type for e in events]
+        assert AiSdkEventType.REASONING_END in types
+
+    def test_convert_tool_event_input_available(self):
+        converter = AiSdkStreamConverter()
+        event = ToolCallEvent(
+            event_type=ToolCallEventType.INPUT_AVAILABLE,
+            tool_call_id="call_1",
+            tool_name="add",
+            arguments={"a": 1, "b": 2},
+        )
+        events = converter.convert_tool_event(event)
+        assert len(events) == 1
+        assert events[0].type == AiSdkEventType.TOOL_INPUT_AVAILABLE
+        assert events[0].payload["toolCallId"] == "call_1"
+        assert events[0].payload["input"] == {"a": 1, "b": 2}
+
+    def test_convert_tool_event_output_available(self):
+        converter = AiSdkStreamConverter()
+        event = ToolCallEvent(
+            event_type=ToolCallEventType.OUTPUT_AVAILABLE,
+            tool_call_id="call_1",
+            tool_name="add",
+            result="3",
+        )
+        events = converter.convert_tool_event(event)
+        assert len(events) == 1
+        assert events[0].type == AiSdkEventType.TOOL_OUTPUT_AVAILABLE
+        assert events[0].payload["output"] == "3"
+
+    def test_convert_tool_event_output_error(self):
+        converter = AiSdkStreamConverter()
+        event = ToolCallEvent(
+            event_type=ToolCallEventType.OUTPUT_ERROR,
+            tool_call_id="call_1",
+            tool_name="add",
+            error="Something went wrong",
+        )
+        events = converter.convert_tool_event(event)
+        assert len(events) == 1
+        assert events[0].type == AiSdkEventType.TOOL_OUTPUT_ERROR
+        assert events[0].payload["errorText"] == "Something went wrong"
+
+    def test_reasoning_not_interrupted_by_empty_content(self):
+        # Minimax and similar models send chunks with both reasoning_content and
+        # delta.content="" simultaneously. Empty content must not close reasoning
+        # blocks or emit useless text-delta events.
+        converter = AiSdkStreamConverter()
+
+        chunk1 = _make_chunk(reasoning_content="The", content="")
+        chunk2 = _make_chunk(reasoning_content=" user", content="")
+        chunk3 = _make_chunk(reasoning_content=" is", content="")
+
+        events1 = converter.convert_chunk(chunk1)
+        events2 = converter.convert_chunk(chunk2)
+        events3 = converter.convert_chunk(chunk3)
+
+        all_types1 = [e.type for e in events1]
+        all_types2 = [e.type for e in events2]
+        all_types3 = [e.type for e in events3]
+
+        # First chunk opens the reasoning block
+        assert AiSdkEventType.REASONING_START in all_types1
+        assert AiSdkEventType.REASONING_DELTA in all_types1
+        # No text events from empty content
+        assert AiSdkEventType.TEXT_START not in all_types1
+        assert AiSdkEventType.TEXT_DELTA not in all_types1
+
+        # Subsequent chunks must NOT re-open reasoning (no start) and must NOT
+        # close reasoning with reasoning-end
+        assert AiSdkEventType.REASONING_START not in all_types2
+        assert AiSdkEventType.REASONING_END not in all_types2
+        assert AiSdkEventType.REASONING_DELTA in all_types2
+        assert AiSdkEventType.TEXT_DELTA not in all_types2
+
+        assert AiSdkEventType.REASONING_START not in all_types3
+        assert AiSdkEventType.REASONING_END not in all_types3
+        assert AiSdkEventType.REASONING_DELTA in all_types3
+        assert AiSdkEventType.TEXT_DELTA not in all_types3
+
+    def test_reset_for_next_step(self):
+        converter = AiSdkStreamConverter()
+        converter._finish_reason = "tool_calls"
+        converter._tool_calls_state = {
+            0: {"id": "x", "name": "y", "arguments": "", "started": True}
+        }
+        converter.reset_for_next_step()
+        assert converter._tool_calls_state == {}
+        assert converter._finish_reason is None
+
+    def test_finish_reason_in_finalize(self):
+        converter = AiSdkStreamConverter()
+        converter.convert_chunk(_make_chunk(content="done", finish_reason="stop"))
+        events = converter.finalize()
+        finish_events = [e for e in events if e.type == AiSdkEventType.FINISH]
+        assert len(finish_events) == 1
+        meta = finish_events[0].payload.get("messageMetadata", {})
+        assert meta.get("finishReason") == "stop"
+
+    def test_tool_input_start_reemitted_after_reset(self):
+        """After reset_for_next_step, tool-input-start must fire again for index 0."""
+        converter = AiSdkStreamConverter()
+
+        tc_round1 = _make_tool_call_delta(
+            index=0, call_id="call_r1", name="search", arguments='{"q":"hi"}'
+        )
+        events_r1 = converter.convert_chunk(_make_chunk(tool_calls=[tc_round1]))
+        starts_r1 = [e for e in events_r1 if e.type == AiSdkEventType.TOOL_INPUT_START]
+        assert len(starts_r1) == 1
+        assert starts_r1[0].payload["toolCallId"] == "call_r1"
+
+        converter.reset_for_next_step()
+
+        tc_round2 = _make_tool_call_delta(
+            index=0, call_id="call_r2", name="search", arguments='{"q":"world"}'
+        )
+        events_r2 = converter.convert_chunk(_make_chunk(tool_calls=[tc_round2]))
+        starts_r2 = [e for e in events_r2 if e.type == AiSdkEventType.TOOL_INPUT_START]
+        assert len(starts_r2) == 1, (
+            "tool-input-start must be re-emitted for index 0 after reset"
+        )
+        assert starts_r2[0].payload["toolCallId"] == "call_r2"
+
+    def test_tool_input_start_not_reemitted_without_reset(self):
+        """Without reset, a second tool call at index 0 must NOT re-emit tool-input-start."""
+        converter = AiSdkStreamConverter()
+
+        tc_round1 = _make_tool_call_delta(
+            index=0, call_id="call_r1", name="search", arguments='{"q":"hi"}'
+        )
+        converter.convert_chunk(_make_chunk(tool_calls=[tc_round1]))
+
+        tc_round2 = _make_tool_call_delta(
+            index=0, call_id="call_r2", name="search", arguments='{"q":"world"}'
+        )
+        events_r2 = converter.convert_chunk(_make_chunk(tool_calls=[tc_round2]))
+        starts_r2 = [e for e in events_r2 if e.type == AiSdkEventType.TOOL_INPUT_START]
+        assert len(starts_r2) == 0, (
+            "Without reset, started=True blocks duplicate tool-input-start"
+        )
diff --git a/libs/core/kiln_ai/adapters/model_adapters/test_structured_output.py b/libs/core/kiln_ai/adapters/model_adapters/test_structured_output.py
index 92d9a1f4d..46fa88aa7 100644
--- a/libs/core/kiln_ai/adapters/model_adapters/test_structured_output.py
+++ b/libs/core/kiln_ai/adapters/model_adapters/test_structured_output.py
@@ -1,7 +1,7 @@
 import json
 from pathlib import Path
 from typing import Dict
-from unittest.mock import Mock, patch
+from unittest.mock import AsyncMock, Mock, patch
 
 import pytest
 from litellm.types.utils import ModelResponse
@@ -10,6 +10,7 @@
 from kiln_ai.adapters.adapter_registry import adapter_for_task
 from kiln_ai.adapters.ml_model_list import built_in_models
 from kiln_ai.adapters.model_adapters.base_adapter import BaseAdapter, RunOutput, Usage
+from kiln_ai.adapters.model_adapters.litellm_adapter import LiteLlmAdapter
 from kiln_ai.adapters.ollama_tools import ollama_online
 from kiln_ai.adapters.test_prompt_adaptors import get_all_models_and_providers
 from kiln_ai.datamodel import PromptId
@@ -53,11 +54,7 @@ def __init__(self, kiln_task: datamodel.Task, response: InputType | None):
         )
         self.response = response
 
-    async def _run(
-        self,
-        input: str,
-        prior_trace=None,
-    ) -> tuple[RunOutput, Usage | None]:
+    async def _run(self, input: str, **kwargs) -> tuple[RunOutput, Usage | None]:
         return RunOutput(output=self.response, intermediate_outputs=None), None
 
     def adapter_name(self) -> str:
@@ -351,9 +348,10 @@ async def test_all_built_in_models_structured_input_mocked(tmp_path):
     mock_config.groq_api_key = "mock_api_key"
 
     with (
-        patch(
-            "litellm.acompletion",
-            side_effect=[mock_response],
+        patch.object(
+            LiteLlmAdapter,
+            "acompletion_checking_response",
+            new=AsyncMock(return_value=(mock_response, mock_response.choices[0])),
         ),
         patch("kiln_ai.utils.config.Config.shared", return_value=mock_config),
     ):
@@ -406,9 +404,15 @@ async def test_structured_input_cot_prompt_builder_mocked(tmp_path):
     mock_config.groq_api_key = "mock_api_key"
 
     with (
-        patch(
-            "litellm.acompletion",
-            side_effect=[mock_response_1, mock_response_2],
+        patch.object(
+            LiteLlmAdapter,
+            "acompletion_checking_response",
+            new=AsyncMock(
+                side_effect=[
+                    (mock_response_1, mock_response_1.choices[0]),
+                    (mock_response_2, mock_response_2.choices[0]),
+                ]
+            ),
         ),
         patch("kiln_ai.utils.config.Config.shared", return_value=mock_config),
     ):
diff --git a/libs/core/kiln_ai/adapters/test_prompt_adaptors.py b/libs/core/kiln_ai/adapters/test_prompt_adaptors.py
index 23dd15b0d..187de1ff2 100644
--- a/libs/core/kiln_ai/adapters/test_prompt_adaptors.py
+++ b/libs/core/kiln_ai/adapters/test_prompt_adaptors.py
@@ -1,9 +1,9 @@
 import os
 from pathlib import Path
-from unittest.mock import patch
+from unittest.mock import AsyncMock, patch
 
 import pytest
-from litellm.utils import ModelResponse
+from litellm.types.utils import ModelResponse
 
 import kiln_ai.datamodel as datamodel
 from kiln_ai.adapters.adapter_registry import adapter_for_task
@@ -113,13 +113,15 @@ async def test_amazon_bedrock(tmp_path):
 
 async def test_mock_returning_run(tmp_path):
     task = build_test_task(tmp_path)
-    with patch("litellm.acompletion") as mock_acompletion:
-        # Configure the mock to return a properly structured response
-        mock_acompletion.return_value = ModelResponse(
-            model="custom_model",
-            choices=[{"message": {"content": "mock response"}}],
-        )
-
+    mock_response = ModelResponse(
+        model="custom_model",
+        choices=[{"message": {"content": "mock response"}}],
+    )
+    with patch.object(
+        LiteLlmAdapter,
+        "acompletion_checking_response",
+        new=AsyncMock(return_value=(mock_response, mock_response.choices[0])),
+    ):
         run_config = KilnAgentRunConfigProperties(
             model_name="custom_model",
             model_provider_name=ModelProviderName.ollama,
diff --git a/libs/core/kiln_ai/adapters/test_prompt_builders.py b/libs/core/kiln_ai/adapters/test_prompt_builders.py
index 25cadd99d..7a67ff5c9 100644
--- a/libs/core/kiln_ai/adapters/test_prompt_builders.py
+++ b/libs/core/kiln_ai/adapters/test_prompt_builders.py
@@ -58,11 +58,7 @@ def test_simple_prompt_builder(tmp_path):
 
 
 class MockAdapter(BaseAdapter):
-    async def _run(
-        self,
-        input: InputType,
-        prior_trace=None,
-    ) -> tuple[RunOutput, Usage | None]:
+    async def _run(self, input: InputType, **kwargs) -> tuple[RunOutput, Usage | None]:
         return RunOutput(output="mock response", intermediate_outputs=None), None
 
     def adapter_name(self) -> str:
diff --git a/libs/core/kiln_ai/datamodel/external_tool_server.py b/libs/core/kiln_ai/datamodel/external_tool_server.py
index b01f6acb0..ad6a6ebdb 100644
--- a/libs/core/kiln_ai/datamodel/external_tool_server.py
+++ b/libs/core/kiln_ai/datamodel/external_tool_server.py
@@ -25,6 +25,18 @@ class ToolServerType(str, Enum):
     kiln_task = "kiln_task"
 
 
+def tool_server_type_to_string(server_type: ToolServerType) -> str:
+    match server_type:
+        case ToolServerType.remote_mcp:
+            return "Remote MCP"
+        case ToolServerType.local_mcp:
+            return "Local MCP"
+        case ToolServerType.kiln_task:
+            return "Kiln Task"
+        case _:
+            raise_exhaustive_enum_error(server_type)
+
+
 class LocalServerProperties(TypedDict, total=True):
     command: str
     args: NotRequired[list[str]]
diff --git a/libs/core/kiln_ai/datamodel/test_basemodel.py b/libs/core/kiln_ai/datamodel/test_basemodel.py
index 03c6dfeaf..897a3749f 100644
--- a/libs/core/kiln_ai/datamodel/test_basemodel.py
+++ b/libs/core/kiln_ai/datamodel/test_basemodel.py
@@ -862,7 +862,7 @@ def individual_lookups():
 class MockAdapter(BaseAdapter):
     """Implementation of BaseAdapter for testing"""
 
-    async def _run(self, input, prior_trace=None):
+    async def _run(self, input, **kwargs):
         return RunOutput(output="test output", intermediate_outputs=None), None
 
     def adapter_name(self) -> str:
diff --git a/libs/core/kiln_ai/tools/mcp_server_tool.py b/libs/core/kiln_ai/tools/mcp_server_tool.py
index 10c1d7820..af93eb949 100644
--- a/libs/core/kiln_ai/tools/mcp_server_tool.py
+++ b/libs/core/kiln_ai/tools/mcp_server_tool.py
@@ -50,9 +50,19 @@ async def run(
     ) -> ToolCallResult:
         result = await self._call_tool(**kwargs)
 
+        # MCP tool returned an application-level error - return it to the agent
+        # instead of crashing the run. This allows the agent to respond gracefully.
         if result.isError:
-            raise ValueError(
-                f"Tool {await self.name()} returned an error: {result.content}"
+            error_text = (
+                " ".join(
+                    block.text
+                    for block in result.content
+                    if isinstance(block, TextContent)
+                )
+                or "Unknown error"
+            )
+            return ToolCallResult(
+                output=json.dumps({"isError": True, "error": error_text})
             )
 
         # If the tool returns structured content, return it as a JSON string
diff --git a/libs/core/kiln_ai/tools/mcp_session_manager.py b/libs/core/kiln_ai/tools/mcp_session_manager.py
index 29ac57c9e..6cde815b1 100644
--- a/libs/core/kiln_ai/tools/mcp_session_manager.py
+++ b/libs/core/kiln_ai/tools/mcp_session_manager.py
@@ -21,10 +21,17 @@
 
 logger = logging.getLogger(__name__)
 
-LOCAL_MCP_ERROR_INSTRUCTION = "Please verify your command, arguments, and environment variables, and consult the server's documentation for the correct setup."
 MCP_SESSION_CACHE_KEY_DELIMITER = "::"
 
 
+class KilnMCPError(RuntimeError):
+    """Wraps MCP connection failures. Unwraps ExceptionGroup; attaches stderr."""
+
+    def __init__(self, message: str, stderr: str = ""):
+        super().__init__(message)
+        self.stderr = stderr
+
+
 class MCPSessionManager:
     """
     This class is a singleton that manages MCP sessions for remote MCP servers.
@@ -410,27 +417,18 @@ def _handle_remote_mcp_error(self, e: Exception) -> NoReturn:
             e: The exception to handle
 
         Raises:
-            ValueError: If the server rejected the request with an HTTP error
-            RuntimeError: If connection to the server failed
+            KilnMCPError: Always, with the raw library error message
         """
-        http_error = self._extract_first_exception(e, httpx.HTTPStatusError)
-        if http_error and isinstance(http_error, httpx.HTTPStatusError):
-            raise ValueError(
-                f"The MCP server rejected the request. "
-                f"Status {http_error.response.status_code}. "
-                f"Response from server:\n{http_error.response.reason_phrase}"
-            ) from e
-
-        connection_error_types = (ConnectionError, OSError, httpx.RequestError)
-        connection_error = self._extract_first_exception(e, connection_error_types)
-        if connection_error and isinstance(connection_error, connection_error_types):
-            raise RuntimeError(
-                f"Unable to connect to MCP server. Please verify the configurations are correct, the server is running, and your network connection is working. Original error: {connection_error}"
-            ) from e
-
-        raise RuntimeError(
-            f"Failed to connect to the MCP Server. Check the server's docs for troubleshooting. Original error: {e}"
-        ) from e
+        for exc_type in (
+            httpx.HTTPStatusError,
+            ConnectionError,
+            OSError,
+            httpx.RequestError,
+        ):
+            found = self._extract_first_exception(e, exc_type)
+            if found:
+                raise KilnMCPError(str(found)) from e
+        raise KilnMCPError(str(e)) from e
 
     def _handle_local_mcp_error(self, e: Exception, stderr: str) -> NoReturn:
         """Shared error handling for local MCP connection failures.
@@ -440,26 +438,13 @@ def _handle_local_mcp_error(self, e: Exception, stderr: str) -> NoReturn:
             stderr: The stderr content from the MCP server
 
         Raises:
-            RuntimeError: Always, with a friendly error message
+            KilnMCPError: Always, with the raw library error message
         """
-        mcp_error = self._extract_first_exception(e, McpError)
-        if mcp_error and isinstance(mcp_error, McpError):
-            self._raise_local_mcp_error(mcp_error, stderr)
-
-        self._raise_local_mcp_error(e, stderr)
-
-    def _raise_local_mcp_error(self, e: Exception, stderr: str) -> NoReturn:
-        """
-        Raise a RuntimeError with a friendlier message for local MCP errors.
-        """
-        error_msg = f"'{e}'"
-
-        if stderr:
-            error_msg += f"\nMCP server error: {stderr}"
-
-        error_msg += f"\n{LOCAL_MCP_ERROR_INSTRUCTION}"
-
-        raise RuntimeError(error_msg) from e
+        for exc_type in (FileNotFoundError, OSError, McpError):
+            found = self._extract_first_exception(e, exc_type)
+            if found:
+                raise KilnMCPError(str(found), stderr=stderr) from e
+        raise KilnMCPError(str(e), stderr=stderr) from e
 
     def _get_path(self) -> str:
         """
diff --git a/libs/core/kiln_ai/tools/test_mcp_server_tool.py b/libs/core/kiln_ai/tools/test_mcp_server_tool.py
index ab113f600..12fe5aaad 100644
--- a/libs/core/kiln_ai/tools/test_mcp_server_tool.py
+++ b/libs/core/kiln_ai/tools/test_mcp_server_tool.py
@@ -1,3 +1,4 @@
+import json
 from unittest.mock import AsyncMock, patch
 
 import pytest
@@ -173,11 +174,50 @@ async def test_run_non_text_content_error(
         with pytest.raises(ValueError, match="First block must be a text block"):
             await tool.run()
 
+    @pytest.mark.asyncio
+    @patch("kiln_ai.tools.mcp_server_tool.get_agent_run_id")
+    @patch("kiln_ai.tools.mcp_server_tool.MCPSessionManager")
+    async def test_run_error_result_no_text_content(
+        self, mock_session_manager, mock_get_run_id
+    ):
+        """Test run() returns Unknown error when isError=True with no TextContent."""
+        mock_get_run_id.return_value = "test_run_123"
+        mock_session = AsyncMock()
+        mock_session_manager.shared.return_value.get_or_create_session = AsyncMock(
+            return_value=mock_session
+        )
+
+        # Return ImageContent instead of TextContent
+        result_content = [
+            ImageContent(type="image", data="base64data", mimeType="image/png")
+        ]
+        call_result = CallToolResult(
+            content=list[ContentBlock](result_content),
+            isError=True,  # type: ignore
+        )
+        mock_session.call_tool.return_value = call_result
+
+        server = ExternalToolServer(
+            name="test_server",
+            type=ToolServerType.remote_mcp,
+            properties={
+                "server_url": "https://example.com",
+                "is_archived": False,
+            },
+        )
+        tool = MCPServerTool(server, "test_tool")
+
+        result = await tool.run()
+
+        # Should return structured error with "Unknown error"
+        expected_output = json.dumps({"isError": True, "error": "Unknown error"})
+        assert result.output == expected_output
+
     @pytest.mark.asyncio
     @patch("kiln_ai.tools.mcp_server_tool.get_agent_run_id")
     @patch("kiln_ai.tools.mcp_server_tool.MCPSessionManager")
     async def test_run_error_result(self, mock_session_manager, mock_get_run_id):
-        """Test run() raises error when tool returns isError=True."""
+        """Test run() returns structured error when tool returns isError=True."""
         mock_get_run_id.return_value = "test_run_123"
         mock_session = AsyncMock()
         mock_session_manager.shared.return_value.get_or_create_session = AsyncMock(
@@ -201,8 +241,11 @@ async def test_run_error_result(self, mock_session_manager, mock_get_run_id):
         )
         tool = MCPServerTool(server, "test_tool")
 
-        with pytest.raises(ValueError, match="Tool test_tool returned an error"):
-            await tool.run()
+        result = await tool.run()
+
+        # Should return structured error, not raise an exception
+        expected_output = json.dumps({"isError": True, "error": "Error occurred"})
+        assert result.output == expected_output
 
     @pytest.mark.asyncio
     @patch("kiln_ai.tools.mcp_server_tool.get_agent_run_id")
diff --git a/libs/core/kiln_ai/tools/test_mcp_session_manager.py b/libs/core/kiln_ai/tools/test_mcp_session_manager.py
index 07c4bc74f..bbf105841 100644
--- a/libs/core/kiln_ai/tools/test_mcp_session_manager.py
+++ b/libs/core/kiln_ai/tools/test_mcp_session_manager.py
@@ -13,8 +13,8 @@
     ToolServerType,
 )
 from kiln_ai.tools.mcp_session_manager import (
-    LOCAL_MCP_ERROR_INSTRUCTION,
     MCP_SESSION_CACHE_KEY_DELIMITER,
+    KilnMCPError,
     MCPSessionManager,
     build_mcp_session_cache_key,
     parse_mcp_session_cache_session_id,
@@ -345,7 +345,7 @@ async def test_session_with_empty_headers(self, mock_client, basic_remote_server
     async def test_remote_mcp_http_status_errors(
         self, mock_client, status_code, reason_phrase, basic_remote_server
     ):
-        """Test remote MCP session handles various HTTP status errors with simplified message."""
+        """Test remote MCP session handles various HTTP status errors with KilnMCPError."""
         # Create HTTP error with specific status code
         response = MagicMock()
         response.status_code = status_code
@@ -359,14 +359,15 @@ async def test_remote_mcp_http_status_errors(
 
         manager = MCPSessionManager.shared()
 
-        # All HTTP errors should now use the simplified message format
-        expected_pattern = f"The MCP server rejected the request. Status {status_code}. Response from server:\n{reason_phrase}"
-        with pytest.raises(
-            ValueError, match=expected_pattern.replace("(", r"\(").replace(")", r"\)")
-        ):
+        # All HTTP errors should now raise KilnMCPError with the raw library message
+        with pytest.raises(KilnMCPError) as exc_info:
             async with manager.mcp_client(basic_remote_server):
                 pass
 
+        # Verify the error message contains the raw library error (the reason phrase)
+        # httpx.HTTPStatusError string representation includes the reason phrase
+        assert reason_phrase in str(exc_info.value)
+
     @pytest.mark.parametrize(
         "connection_error_type,error_message",
         [
@@ -380,7 +381,7 @@ async def test_remote_mcp_http_status_errors(
     async def test_remote_mcp_connection_errors(
         self, mock_client, connection_error_type, error_message, basic_remote_server
     ):
-        """Test remote MCP session handles various connection errors with simplified message."""
+        """Test remote MCP session handles various connection errors with KilnMCPError."""
         # Create connection error
         if connection_error_type == httpx.RequestError:
             connection_error = connection_error_type(error_message, request=MagicMock())
@@ -394,8 +395,8 @@ async def test_remote_mcp_connection_errors(
 
         manager = MCPSessionManager.shared()
 
-        # All connection errors should use the simplified message format
-        with pytest.raises(RuntimeError, match="Unable to connect to MCP server"):
+        # All connection errors should now raise KilnMCPError
+        with pytest.raises(KilnMCPError):
             async with manager.mcp_client(basic_remote_server):
                 pass
 
@@ -424,13 +425,14 @@ def __init__(self, exceptions):
 
         manager = MCPSessionManager.shared()
 
-        # Should extract the HTTP error from the nested structure
-        with pytest.raises(
-            ValueError, match=r"The MCP server rejected the request. Status 401"
-        ):
+        # Should extract the HTTP error from the nested structure and raise KilnMCPError
+        with pytest.raises(KilnMCPError) as exc_info:
             async with manager.mcp_client(basic_remote_server):
                 pass
 
+        # Verify the error message contains the raw library error (the reason phrase)
+        assert "Unauthorized" in str(exc_info.value)
+
     @patch("kiln_ai.tools.mcp_session_manager.streamablehttp_client")
     async def test_remote_mcp_connection_error_in_nested_exceptions(
         self, mock_client, basic_remote_server
@@ -451,8 +453,8 @@ def __init__(self, exceptions):
 
         manager = MCPSessionManager.shared()
 
-        # Should extract the connection error from the nested structure
-        with pytest.raises(RuntimeError, match="Unable to connect to MCP server"):
+        # Should extract the connection error from the nested structure and raise KilnMCPError
+        with pytest.raises(KilnMCPError):
             async with manager.mcp_client(basic_remote_server):
                 pass
 
@@ -460,18 +462,21 @@ def __init__(self, exceptions):
     async def test_remote_mcp_unknown_error_fallback(
         self, mock_client, basic_remote_server
     ):
-        """Test remote MCP session handles unknown errors with fallback message."""
+        """Test remote MCP session handles unknown errors with KilnMCPError."""
         # Mock client to raise an unknown error type
         unknown_error = RuntimeError("Unexpected error")
         mock_client.return_value.__aenter__.side_effect = unknown_error
 
         manager = MCPSessionManager.shared()
 
-        # Should use the fallback error message
-        with pytest.raises(RuntimeError, match="Failed to connect to the MCP Server"):
+        # Should raise KilnMCPError with the raw library message
+        with pytest.raises(KilnMCPError) as exc_info:
             async with manager.mcp_client(basic_remote_server):
                 pass
 
+        # Verify the error message contains the raw error
+        assert "Unexpected error" in str(exc_info.value)
+
     @patch("kiln_ai.tools.mcp_session_manager.streamablehttp_client")
     @patch("kiln_ai.utils.config.Config.shared")
     async def test_session_with_secret_headers(
@@ -1103,10 +1108,10 @@ def mock_get_value(key):
         ],
     )
     @patch("kiln_ai.tools.mcp_session_manager.stdio_client")
-    async def test_local_mcp_various_errors_use_simplified_message(
+    async def test_local_mcp_various_errors_use_raw_message(
         self, mock_client, error_type, error_message, basic_local_server
     ):
-        """Test local MCP session handles various errors with simplified message."""
+        """Test local MCP session handles various errors with KilnMCPError using raw library messages."""
         # Create the appropriate error
         if error_type == McpError:
             error_data = ErrorData(code=-1, message=error_message)
@@ -1119,11 +1124,14 @@ async def test_local_mcp_various_errors_use_simplified_message(
 
         manager = MCPSessionManager.shared()
 
-        # All local errors should now use the simplified message format
-        with pytest.raises(RuntimeError, match=LOCAL_MCP_ERROR_INSTRUCTION):
+        # All error types should raise KilnMCPError with the raw library message
+        with pytest.raises(KilnMCPError) as exc_info:
             async with manager.mcp_client(basic_local_server):
                 pass
 
+        # Verify the error message contains the raw library error message
+        assert error_message in str(exc_info.value)
+
     @patch("kiln_ai.tools.mcp_session_manager.stdio_client")
     async def test_local_mcp_mcp_error_in_nested_exceptions(self, mock_client):
         """Test local MCP session extracts McpError from nested exceptions."""
@@ -1155,33 +1163,13 @@ def __init__(self, exceptions):
 
         manager = MCPSessionManager.shared()
 
-        # Should extract the McpError from the nested structure and use simplified message
-        with pytest.raises(RuntimeError, match=LOCAL_MCP_ERROR_INSTRUCTION):
+        # Should extract the McpError from the nested structure and raise KilnMCPError
+        with pytest.raises(KilnMCPError) as exc_info:
             async with manager.mcp_client(tool_server):
                 pass
 
-    def test_raise_local_mcp_error_method(self):
-        """Test the _raise_local_mcp_error helper method."""
-        manager = MCPSessionManager()
-
-        # Test with different exception types
-        test_exceptions = [
-            ValueError("test value error"),
-            FileNotFoundError("file not found"),
-            RuntimeError("runtime error"),
-            Exception("generic exception"),
-        ]
-
-        for original_error in test_exceptions:
-            with pytest.raises(RuntimeError) as exc_info:
-                manager._raise_local_mcp_error(original_error, "")
-
-            # Check that the error message contains expected text
-            assert LOCAL_MCP_ERROR_INSTRUCTION in str(exc_info.value)
-            assert str(original_error) in str(exc_info.value)
-
-            # Check that the original exception is chained
-            assert exc_info.value.__cause__ is original_error
+        # Verify the error message contains the raw library error
+        assert "Server startup failed" in str(exc_info.value)
 
     @patch("kiln_ai.tools.mcp_session_manager.stdio_client")
     @patch("kiln_ai.utils.config.Config.shared")
@@ -1562,6 +1550,29 @@ async def test_list_tools_with_real_local_mcp_server(self):
         assert len(tools.tools) > 0
         assert "firecrawl_scrape" in [tool.name for tool in tools.tools]
 
+    async def test_local_mcp_nonexistent_command_raises_kiln_mcp_error(self):
+        """Real integration test (no mocks): confirms that spawning a local MCP server
+        with a nonexistent command always raises KilnMCPError, not FileNotFoundError
+        or OSError. Validates that callers can safely catch (KilnMCPError, RuntimeError, ValueError)
+        to handle all local MCP failure modes."""
+        server = ExternalToolServer(
+            name="bad_command_server",
+            type=ToolServerType.local_mcp,
+            description="Server with nonexistent command",
+            properties={
+                "command": "this_command_does_not_exist_kiln_test",
+                "args": [],
+                "env_vars": {},
+                "secret_env_var_keys": [],
+                "is_archived": False,
+            },
+        )
+
+        # Should now raise KilnMCPError (subclass of RuntimeError)
+        with pytest.raises(KilnMCPError):
+            async with MCPSessionManager.shared().mcp_client(server) as session:
+                await session.list_tools()
+
 
 @pytest.fixture
 def mock_mcp_streams():
diff --git a/libs/core/kiln_ai/utils/config.py b/libs/core/kiln_ai/utils/config.py
index 704c9f87f..2fe8f0f73 100644
--- a/libs/core/kiln_ai/utils/config.py
+++ b/libs/core/kiln_ai/utils/config.py
@@ -20,6 +20,7 @@ def __init__(
         default_lambda: Optional[Callable[[], Any]] = None,
         sensitive: bool = False,
         sensitive_keys: Optional[List[str]] = None,
+        in_memory: bool = False,
     ):
         self.type = type_
         self.default = default
@@ -27,6 +28,7 @@ def __init__(
         self.default_lambda = default_lambda
         self.sensitive = sensitive
         self.sensitive_keys = sensitive_keys
+        self.in_memory = in_memory
 
 
 class Config:
@@ -43,6 +45,7 @@ def __init__(self, properties: Dict[str, ConfigProperty] | None = None):
                 bool,
                 env_var="KILN_AUTOSAVE_RUNS",
                 default=True,
+                in_memory=True,
             ),
             "open_ai_api_key": ConfigProperty(
                 str,
@@ -198,6 +201,7 @@ def __init__(self, properties: Dict[str, ConfigProperty] | None = None):
             ),
         }
         self._lock = threading.Lock()
+        self._in_memory_settings: Dict[str, Any] = {}
         self._settings = self.load_settings()
 
     @classmethod
@@ -221,10 +225,14 @@ def __getattr__(self, name: str) -> Any:
 
         property_config = self._properties[name]
 
-        # Check if the value is in settings
-        if name in self._settings:
-            value = self._settings[name]
-            return value if value is None else property_config.type(value)
+        if property_config.in_memory:
+            if name in self._in_memory_settings:
+                value = self._in_memory_settings[name]
+                return value if value is None else property_config.type(value)
+        else:
+            if name in self._settings:
+                value = self._settings[name]
+                return value if value is None else property_config.type(value)
 
         # Check environment variable
         if property_config.env_var and property_config.env_var in os.environ:
@@ -240,10 +248,14 @@ def __getattr__(self, name: str) -> Any:
         return None if value is None else property_config.type(value)
 
     def __setattr__(self, name, value):
-        if name in ("_properties", "_settings", "_lock"):
+        if name in ("_properties", "_settings", "_lock", "_in_memory_settings"):
             super().__setattr__(name, value)
         elif name in self._properties:
-            self.update_settings({name: value})
+            if self._properties[name].in_memory:
+                with self._lock:
+                    self._in_memory_settings[name] = value
+            else:
+                self.update_settings({name: value})
         else:
             raise AttributeError(f"Config has no attribute '{name}'")
 
@@ -268,14 +280,22 @@ def load_settings(cls):
         return settings
 
     def settings(self, hide_sensitive=False) -> Dict[str, Any]:
+        with self._lock:
+            filtered_disk = {
+                k: v
+                for k, v in self._settings.items()
+                if k not in self._properties or not self._properties[k].in_memory
+            }
+            combined = {**filtered_disk, **self._in_memory_settings}
+
         if not hide_sensitive:
-            return self._settings
+            return combined
 
         settings = {
             k: "[hidden]"
             if k in self._properties and self._properties[k].sensitive
             else copy.deepcopy(v)
-            for k, v in self._settings.items()
+            for k, v in combined.items()
         }
         # Hide sensitive keys in lists. Could generalize this if we every have more types, but right not it's only needed for root elements of lists
         for key, value in settings.items():
@@ -293,18 +313,32 @@ def save_setting(self, name: str, value: Any):
         self.update_settings({name: value})
 
     def update_settings(self, new_settings: Dict[str, Any]):
-        # Lock to prevent race conditions in multi-threaded scenarios
         with self._lock:
-            # Fresh load to avoid clobbering changes from other instances
-            current_settings = self.load_settings()
-            current_settings.update(new_settings)
-            # remove None values
-            current_settings = {
-                k: v for k, v in current_settings.items() if v is not None
+            in_memory_updates = {
+                k: v
+                for k, v in new_settings.items()
+                if k in self._properties and self._properties[k].in_memory
             }
-            with open(self.settings_path(), "w") as f:
-                yaml.dump(current_settings, f)
-            self._settings = current_settings
+            disk_updates = {
+                k: v
+                for k, v in new_settings.items()
+                if k not in self._properties or not self._properties[k].in_memory
+            }
+
+            if in_memory_updates:
+                self._in_memory_settings.update(in_memory_updates)
+
+            if disk_updates:
+                # Fresh load to avoid clobbering changes from other instances
+                current_settings = self.load_settings()
+                current_settings.update(disk_updates)
+                # remove None values
+                current_settings = {
+                    k: v for k, v in current_settings.items() if v is not None
+                }
+                with open(self.settings_path(), "w") as f:
+                    yaml.dump(current_settings, f)
+                self._settings = current_settings
 
 
 def _get_user_id():
diff --git a/libs/core/kiln_ai/utils/test_config.py b/libs/core/kiln_ai/utils/test_config.py
index 75891fe88..5da2302e1 100644
--- a/libs/core/kiln_ai/utils/test_config.py
+++ b/libs/core/kiln_ai/utils/test_config.py
@@ -494,3 +494,206 @@ def test_mcp_secrets_type_validation():
     assert config.mcp_secrets == mixed_types or config.mcp_secrets == {
         "server::key": "123"
     }
+
+
+def test_in_memory_property_default_value(mock_yaml_file):
+    """Test that in-memory property returns default value"""
+    with patch(
+        "kiln_ai.utils.config.Config.settings_path",
+        return_value=mock_yaml_file,
+    ):
+        config = Config(
+            properties={
+                "in_memory_prop": ConfigProperty(bool, default=True, in_memory=True),
+            }
+        )
+        assert config.in_memory_prop is True
+
+
+def test_in_memory_property_env_var(mock_yaml_file):
+    """Test that in-memory property respects env var"""
+    with (
+        patch(
+            "kiln_ai.utils.config.Config.settings_path",
+            return_value=mock_yaml_file,
+        ),
+        patch.dict(os.environ, {"IN_MEMORY_TEST_VAR": "custom_env_value"}),
+    ):
+        config = Config(
+            properties={
+                "in_memory_prop": ConfigProperty(
+                    str,
+                    default="default_value",
+                    env_var="IN_MEMORY_TEST_VAR",
+                    in_memory=True,
+                ),
+            }
+        )
+        assert config.in_memory_prop == "custom_env_value"
+
+
+def test_in_memory_property_setter_works(mock_yaml_file):
+    """Test that in-memory property setter works"""
+    with patch(
+        "kiln_ai.utils.config.Config.settings_path",
+        return_value=mock_yaml_file,
+    ):
+        config = Config(
+            properties={
+                "in_memory_prop": ConfigProperty(bool, default=True, in_memory=True),
+            }
+        )
+        assert config.in_memory_prop is True
+        config.in_memory_prop = False
+        assert config.in_memory_prop is False
+
+
+def test_in_memory_property_not_persisted_to_yaml(mock_yaml_file):
+    """Test that in-memory property is not persisted to YAML"""
+    with patch(
+        "kiln_ai.utils.config.Config.settings_path",
+        return_value=mock_yaml_file,
+    ):
+        config = Config(
+            properties={
+                "in_memory_prop": ConfigProperty(bool, default=True, in_memory=True),
+                "persisted_prop": ConfigProperty(str, default="default"),
+            }
+        )
+        config.in_memory_prop = False
+        config.persisted_prop = "persisted_value"
+
+        with open(mock_yaml_file, "r") as f:
+            saved_settings = yaml.safe_load(f)
+
+        assert "in_memory_prop" not in saved_settings
+        assert saved_settings["persisted_prop"] == "persisted_value"
+
+
+def test_in_memory_property_included_in_settings_output(mock_yaml_file):
+    """Test that in-memory property is included in settings() output"""
+    with patch(
+        "kiln_ai.utils.config.Config.settings_path",
+        return_value=mock_yaml_file,
+    ):
+        config = Config(
+            properties={
+                "in_memory_prop": ConfigProperty(bool, default=True, in_memory=True),
+                "persisted_prop": ConfigProperty(str, default="default"),
+            }
+        )
+        config.in_memory_prop = False
+        config.persisted_prop = "persisted_value"
+
+        settings = config.settings()
+        assert settings["in_memory_prop"] is False
+        assert settings["persisted_prop"] == "persisted_value"
+
+
+def test_in_memory_property_priority(mock_yaml_file):
+    """Test that setter takes precedence over env var for in-memory properties"""
+    with (
+        patch(
+            "kiln_ai.utils.config.Config.settings_path",
+            return_value=mock_yaml_file,
+        ),
+        patch.dict(os.environ, {"IN_MEMORY_TEST_VAR": "env_value"}),
+    ):
+        config = Config(
+            properties={
+                "in_memory_prop": ConfigProperty(
+                    str,
+                    default="default_value",
+                    env_var="IN_MEMORY_TEST_VAR",
+                    in_memory=True,
+                ),
+            }
+        )
+        assert config.in_memory_prop == "env_value"
+
+        config.in_memory_prop = "set_value"
+        assert config.in_memory_prop == "set_value"
+
+
+def test_autosave_runs_is_in_memory():
+    """Test that autosave_runs is an in-memory property"""
+    config = Config.shared()
+    assert config._properties["autosave_runs"].in_memory is True
+    assert config.autosave_runs is True
+
+
+def test_update_settings_filters_in_memory_properties(mock_yaml_file):
+    """Test that update_settings routes in-memory properties correctly"""
+    with patch(
+        "kiln_ai.utils.config.Config.settings_path",
+        return_value=mock_yaml_file,
+    ):
+        config = Config(
+            properties={
+                "in_memory_prop": ConfigProperty(bool, default=True, in_memory=True),
+                "persisted_prop": ConfigProperty(str, default="default"),
+            }
+        )
+
+        config.update_settings(
+            {
+                "in_memory_prop": False,
+                "persisted_prop": "updated_value",
+            }
+        )
+
+        assert config.in_memory_prop is False
+        assert config.persisted_prop == "updated_value"
+
+        with open(mock_yaml_file, "r") as f:
+            saved_settings = yaml.safe_load(f)
+
+        assert "in_memory_prop" not in saved_settings
+        assert saved_settings["persisted_prop"] == "updated_value"
+
+
+def test_save_setting_filters_in_memory_properties(mock_yaml_file):
+    """Test that save_setting routes in-memory properties correctly"""
+    with patch(
+        "kiln_ai.utils.config.Config.settings_path",
+        return_value=mock_yaml_file,
+    ):
+        config = Config(
+            properties={
+                "in_memory_prop": ConfigProperty(bool, default=True, in_memory=True),
+            }
+        )
+
+        config.save_setting("in_memory_prop", False)
+
+        assert config.in_memory_prop is False
+
+        assert not os.path.exists(mock_yaml_file)
+
+
+def test_in_memory_property_sensitive_hidden(mock_yaml_file):
+    """Test that sensitive in-memory properties are hidden in settings()"""
+    with patch(
+        "kiln_ai.utils.config.Config.settings_path",
+        return_value=mock_yaml_file,
+    ):
+        config = Config(
+            properties={
+                "in_memory_secret": ConfigProperty(
+                    str, default="default", in_memory=True, sensitive=True
+                ),
+                "in_memory_public": ConfigProperty(
+                    str, default="default", in_memory=True
+                ),
+            }
+        )
+        config.in_memory_secret = "secret_value"
+        config.in_memory_public = "public_value"
+
+        settings = config.settings(hide_sensitive=True)
+        assert settings["in_memory_secret"] == "[hidden]"
+        assert settings["in_memory_public"] == "public_value"
+
+        settings_visible = config.settings(hide_sensitive=False)
+        assert settings_visible["in_memory_secret"] == "secret_value"
+        assert settings_visible["in_memory_public"] == "public_value"
diff --git a/libs/core/pyproject.toml b/libs/core/pyproject.toml
index 72d673630..d96bd594a 100644
--- a/libs/core/pyproject.toml
+++ b/libs/core/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "kiln-ai"
-version = "0.24.0"
+version = "0.25.0"
 requires-python = ">=3.10"
 readme = "README.md"
 description = 'Kiln AI'
@@ -41,8 +41,8 @@ dependencies = [
     "pillow>=11.1.0",
     "llama-index-vector-stores-lancedb>=0.4.2",
     "mcp[cli]>=1.10.1",
-    "litellm>=1.80.9",
     "typer>=0.9.0",
+    "litellm>=1.81.16",
 ]
 
 [project.scripts]
diff --git a/libs/server/kiln_server/run_api.py b/libs/server/kiln_server/run_api.py
index ea13104d2..f123d421e 100644
--- a/libs/server/kiln_server/run_api.py
+++ b/libs/server/kiln_server/run_api.py
@@ -56,10 +56,6 @@ class RunTaskRequest(BaseModel):
     plaintext_input: str | None = None
     structured_input: StructuredInputType | None = None
     tags: list[str] | None = None
-    task_run_id: str | None = Field(
-        default=None,
-        description="When set, continue an existing session. The new message is appended to the run's trace.",
-    )
 
     # Allows use of the model_name field (usually pydantic will reserve model_*)
     model_config = ConfigDict(protected_namespaces=())
@@ -285,28 +281,7 @@ async def run_task(
                 detail="No input provided. Ensure your provided the proper format (plaintext or structured).",
             )
 
-        existing_run: TaskRun | None = None
-        if request.task_run_id is not None:
-            if task.path is None:
-                raise HTTPException(
-                    status_code=400,
-                    detail="Cannot continue session: task has no path. Save the task first.",
-                )
-            existing_run = TaskRun.from_id_and_parent_path(
-                request.task_run_id, task.path
-            )
-            if existing_run is None:
-                raise HTTPException(
-                    status_code=404,
-                    detail="Run not found. Cannot continue session.",
-                )
-            if not existing_run.trace or len(existing_run.trace) == 0:
-                raise HTTPException(
-                    status_code=400,
-                    detail="Run has no trace. Cannot continue session without conversation history.",
-                )
-
-        return await adapter.invoke(input, existing_run=existing_run)
+        return await adapter.invoke(input)
 
     @app.patch("/api/projects/{project_id}/tasks/{task_id}/runs/{run_id}")
     async def update_run(
diff --git a/libs/server/kiln_server/test_run_api.py b/libs/server/kiln_server/test_run_api.py
index 608a03a94..974f1d433 100644
--- a/libs/server/kiln_server/test_run_api.py
+++ b/libs/server/kiln_server/test_run_api.py
@@ -143,135 +143,6 @@ async def test_run_task_success(client, task_run_setup):
     assert res["id"] is not None
 
 
-@pytest.mark.asyncio
-async def test_run_task_with_task_run_id_continues_session(client, task_run_setup):
-    """Test that run_task with task_run_id passes it to adapter.invoke for session continuation."""
-    project = task_run_setup["project"]
-    task = task_run_setup["task"]
-    task_run = task_run_setup["task_run"]
-
-    run_task_request = {
-        "run_config_properties": {
-            "model_name": "gpt_4o",
-            "model_provider_name": "ollama",
-            "prompt_id": "simple_prompt_builder",
-            "structured_output_mode": "json_schema",
-        },
-        "plaintext_input": "Follow-up message",
-        "task_run_id": task_run.id,
-    }
-
-    continued_run = TaskRun(
-        parent=task,
-        input=task_run.input,
-        input_source=task_run.input_source,
-        output=TaskOutput(
-            output="Continued response",
-            source=task_run.output.source,
-        ),
-    )
-    continued_run.id = task_run.id
-
-    with (
-        patch("kiln_server.run_api.task_from_id") as mock_task_from_id,
-        patch.object(LiteLlmAdapter, "invoke", new_callable=AsyncMock) as mock_invoke,
-        patch("kiln_ai.utils.config.Config.shared") as MockConfig,
-    ):
-        mock_task_from_id.return_value = task
-        mock_invoke.return_value = continued_run
-
-        mock_config_instance = MockConfig.return_value
-        mock_config_instance.ollama_base_url = "http://localhost:11434/v1"
-
-        response = client.post(
-            f"/api/projects/{project.id}/tasks/{task.id}/run", json=run_task_request
-        )
-
-    assert response.status_code == 200
-    mock_invoke.assert_called_once()
-    call_kwargs = mock_invoke.call_args[1]
-    assert call_kwargs["existing_run"].id == task_run.id
-    assert mock_invoke.call_args[0][0] == "Follow-up message"
-    res = response.json()
-    assert res["output"]["output"] == "Continued response"
-
-
-@pytest.mark.asyncio
-async def test_run_task_task_run_id_not_found_returns_404(client, task_run_setup):
-    """Test that run_task with nonexistent task_run_id returns 404."""
-    project = task_run_setup["project"]
-    task = task_run_setup["task"]
-
-    run_task_request = {
-        "run_config_properties": {
-            "model_name": "gpt_4o",
-            "model_provider_name": "ollama",
-            "prompt_id": "simple_prompt_builder",
-            "structured_output_mode": "json_schema",
-        },
-        "plaintext_input": "Follow-up",
-        "task_run_id": "nonexistent-run-id",
-    }
-
-    with patch("kiln_server.run_api.task_from_id") as mock_task_from_id:
-        mock_task_from_id.return_value = task
-        response = client.post(
-            f"/api/projects/{project.id}/tasks/{task.id}/run", json=run_task_request
-        )
-
-    assert response.status_code == 404
-    assert "Run not found" in response.json()["message"]
-
-
-@pytest.mark.asyncio
-async def test_run_task_task_run_id_no_trace_returns_400(client, task_run_setup):
-    """Test that run_task with task_run_id for run without trace returns 400."""
-    project = task_run_setup["project"]
-    task = task_run_setup["task"]
-
-    task_run_no_trace = TaskRun(
-        parent=task,
-        input="Hello",
-        input_source=DataSource(
-            type=DataSourceType.human, properties={"created_by": "Test User"}
-        ),
-        output=TaskOutput(
-            output="Hi",
-            source=DataSource(
-                type=DataSourceType.synthetic,
-                properties={
-                    "model_name": "gpt_4o",
-                    "model_provider": "ollama",
-                    "adapter_name": "kiln_langchain_adapter",
-                    "prompt_id": "simple_prompt_builder",
-                },
-            ),
-        ),
-        trace=None,
-    )
-    task_run_no_trace.save_to_file()
-
-    run_task_request = {
-        "run_config_properties": {
-            "model_name": "gpt_4o",
-            "model_provider_name": "ollama",
-            "prompt_id": "simple_prompt_builder",
-            "structured_output_mode": "json_schema",
-        },
-        "plaintext_input": "Follow-up",
-        "task_run_id": task_run_no_trace.id,
-    }
-
-    with patch("kiln_server.run_api.task_from_id") as mock_task_from_id:
-        mock_task_from_id.return_value = task
-        response = client.post(
-            f"/api/projects/{project.id}/tasks/{task.id}/run", json=run_task_request
-        )
-
-    assert response.status_code == 400
-    assert "no trace" in response.json()["message"].lower()
-
-
 @pytest.mark.asyncio
 async def test_run_task_structured_output(client, task_run_setup):
     task = task_run_setup["task"]
@@ -1918,7 +1789,7 @@ def _assert_math_tools_response(res: dict, expected_in_output: str) -> None:
 async def test_run_task_adapter_sanity_math_tools(
     client, adapter_sanity_check_math_tools_setup
 ):
-    """Multi-turn run with built-in Kiln math tools. Test that tools + continue session work as expected."""
+    """Multiple runs with built-in Kiln math tools. Test that tools work across independent runs."""
     if not os.environ.get("OPENROUTER_API_KEY"):
         pytest.skip("OPENROUTER_API_KEY required for this test")
 
@@ -1950,19 +1821,16 @@ async def test_run_task_adapter_sanity_math_tools(
     assert response1.status_code == 200
     res1 = response1.json()
     _assert_math_tools_response(res1, "4")
-    task_run_id = res1["id"]
 
     response2 = client.post(
         f"/api/projects/{project.id}/tasks/{task.id}/run",
         json={
             "run_config_properties": run_config,
             "plaintext_input": "What is 3 times 4? Use the tools to calculate.",
-            "task_run_id": task_run_id,
         },
     )
     assert response2.status_code == 200
     res2 = response2.json()
-    assert res2["id"] == task_run_id
     _assert_math_tools_response(res2, "12")
 
     response3 = client.post(
@@ -1970,24 +1838,19 @@ async def test_run_task_adapter_sanity_math_tools(
         json={
             "run_config_properties": run_config,
             "plaintext_input": "What is 7 times 8 plus 3? Use the tools to calculate.",
-            "task_run_id": task_run_id,
         },
     )
     assert response3.status_code == 200
     res3 = response3.json()
-    assert res3["id"] == task_run_id
     _assert_math_tools_response(res3, "59")
 
-    # now ask it to list out all the previous results in an array
     response4 = client.post(
         f"/api/projects/{project.id}/tasks/{task.id}/run",
         json={
             "run_config_properties": run_config,
-            "plaintext_input": "List all the previous results in an array - e.g. [55, 81, 7].",
-            "task_run_id": task_run_id,
+            "plaintext_input": "What is 10 minus 3? Use the tools to calculate.",
         },
     )
     assert response4.status_code == 200
     res4 = response4.json()
-    assert res4["id"] == task_run_id
-    assert res4["output"]["output"] == "[4, 12, 59]"
+    _assert_math_tools_response(res4, "7")
diff --git a/libs/server/pyproject.toml b/libs/server/pyproject.toml
index 8514c529f..a653f650a 100644
--- a/libs/server/pyproject.toml
+++ b/libs/server/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "kiln-server"
-version = "0.24.0"
+version = "0.25.0"
 requires-python = ">=3.10"
 description = 'Kiln AI Server'
 readme = "README.md"
diff --git a/pyproject.toml b/pyproject.toml
index 652c995d2..2c9a1b632 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -23,7 +23,7 @@ dev = [
     "ruff>=0.15.0",
     "watchfiles>=1.1.0",
     "scalar-fastapi>=1.4.3",
-    "ty>=0.0.2",
+    "ty==0.0.8",
 ]
 
 [tool.uv]
diff --git a/uv.lock b/uv.lock
index e74173fea..4dd1f62fc 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1295,31 +1295,34 @@ wheels = [
 
 [[package]]
 name = "hf-xet"
-version = "1.2.0"
+version = "1.3.1"
 source = { registry = "https://pypi.org/simple" }
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