Merge branch 'main' into fix/dbt-stderr-on-failure-only

Author: b-per

.changes/unreleased/Bug Fix-20260410-order-by-grain.yaml

@@ -0,0 +1,3 @@
+kind: Bug Fix
+body: Add optional grain field to order_by in query_metrics; when provided it takes precedence over the matching group_by grain, preserving backward-compatible fallback when omitted
+time: 2026-04-10T13:45:00.000000-07:00

.changes/unreleased/Bug Fix-20260507-184213.yaml

@@ -0,0 +1,3 @@
+kind: Bug Fix
+body: 'fix: list_tools no longer triggers host elicitation, preventing ''No tools'' in dbt Core (CLI-only) setups after v1.17.0'
+time: 2026-05-07T18:42:13.228292+02:00

.changes/unreleased/Enhancement or New Feature-20260511-101749.yaml

@@ -0,0 +1,3 @@
+kind: Enhancement or New Feature
+body: 'list_metrics now accepts a list of substrings in the search parameter (results are unioned and deduplicated, fetched in parallel) and prefixes its CSV with a # Note: line whenever description/metadata are trimmed because the response exceeded DBT_MCP_SL_MAX_RESPONSE_CHARS. Trimming is also now scoped to broad listings (result count above metrics_related_max) so a narrow result set always returns full description and metadata.'
+time: 2026-05-11T10:17:49.495415+02:00

.changes/unreleased/Under the Hood-20260128-110230.yaml

@@ -0,0 +1,3 @@
+kind: Under the Hood
+body: Sign release PR commits with github-actions bot for verified commit signatures
+time: 2026-01-28T11:02:30.412674+01:00

.github/workflows/create-release-pr.yml

@@ -94,6 +94,7 @@ jobs:
       - name: Create Pull Request
         uses: peter-evans/create-pull-request@271a8d0340265f705b14b6d32b9829c1cb33d45e
         with:
+          committer: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
           title: "version: ${{ steps.package-version.outputs.version }}"
           branch: release/${{ steps.package-version.outputs.version }}
           commit-message: |

src/dbt_mcp/mcp/server.py

@@ -68,7 +68,7 @@ async def _is_multi_project(self) -> bool:
             (
                 settings,
                 _,
-            ) = await self.config.credentials_provider.get_credentials()
+            ) = await self.config.credentials_provider.inner_provider.get_credentials()
         except MissingHostError as e:
             logger.warning(
                 "Could not resolve credentials — defaulting to single-project mode: %s",

src/dbt_mcp/prompts/semantic_layer/list_metrics.md

@@ -6,5 +6,7 @@ When the number of metrics is below the configured threshold (default: 10), each
 
 When above the threshold, only metrics are returned. `metric_time` is a standard time dimension available on most metrics — you can often query directly without calling `get_dimensions` first. Call `get_dimensions` only when you need non-time dimensions or specific granularity details.
 
+For broad listings that exceed the size budget, the `description` and `metadata` columns are dropped to save tokens and the CSV is prefixed with one or more `# Note:` lines explaining what happened. When that happens, call `list_metrics` again with the `search` parameter to retrieve those fields for the specific metrics you care about — a narrow result set (at or below the related-metrics threshold) is always returned with full `description` and `metadata`, even if the text is verbose. `search` accepts either a single substring or a list of substrings; when a list is provided, metrics whose name matches **any** of the substrings are returned (deduplicated), so you can fetch details for several metrics in one call.
+
 If the user is asking a data-related or business-related question, use this tool as a first step.
 

src/dbt_mcp/prompts/semantic_layer/query_metrics.md

@@ -7,8 +7,12 @@ entities to provide. You can call the list_metrics, get_dimensions,
 and get_entities tools to get information about which metrics, dimensions,
 and entities to use.
 
-When using the `order_by` parameter, you must ensure that the dimension or
-entity also appears in the `group_by` parameter. When fulfilling a lookback
+When using the `order_by` parameter, each item must refer to either a metric
+name or a field that also appears in `group_by`. For time dimensions, you may
+specify a `grain` in `order_by` independently from `group_by`; if omitted, it
+defaults to the grain of the matching `group_by` entry. `grain` only applies to
+time dimensions and should be omitted for metrics and categorical dimensions.
+When fulfilling a lookback
 query, prefer using order_by and limit instead of using the where parameter.
 A lookback query requires that the `order_by` parameter includes a descending
 order for a time dimension.
@@ -53,7 +57,7 @@ Thinking step-by-step:
 Parameters:
     metrics=["total_sales"]
     group_by=[{"name": "metric_time", "grain": "MONTH", "type": "time_dimension"}]
-    order_by=[{"name": "metric_time", "descending": true}]
+    order_by=[{"name": "metric_time", "grain": "MONTH", "descending": true}]
     limit=1
 </example>
 <example>
@@ -72,12 +76,12 @@ Thinking step-by-step:
 Parameters:
     metrics=["revenue"]
     group_by=[{"name": "customer_name", "type": "dimension"}, {"name": "metric_time", "grain": "QUARTER", "type": "time_dimension"}]
-    order_by=[{"name": "metric_time", "descending": true}, {"name": "revenue", "descending": true}]
+    order_by=[{"name": "metric_time", "grain": "QUARTER", "descending": true}, {"name": "revenue", "descending": true}]
     limit=5
 Follow-up Query (after verifying results):
     metrics=["revenue"]
     group_by=[{"name": "customer_name", "type": "dimension"}, {"name": "metric_time", "grain": "QUARTER", "type": "time_dimension"}]
-    order_by=[{"name": "metric_time", "descending": true}, {"name": "revenue", "descending": true}]
+    order_by=[{"name": "metric_time", "grain": "QUARTER", "descending": true}, {"name": "revenue", "descending": true}]
     limit=null
 </example>
 <example>
@@ -116,13 +120,13 @@ Thinking step-by-step:
 Parameters (initial query):
     metrics=["new_users"]
     group_by=[{"name": "metric_time", "grain": "WEEK", "type": "time_dimension"}]
-    order_by=[{"name": "metric_time", "descending": false}]
+    order_by=[{"name": "metric_time", "grain": "WEEK", "descending": false}]
     where="{{ TimeDimension('metric_time', 'WEEK') }} >= '2023-01-01' AND {{ TimeDimension('metric_time', 'WEEK') }} < '2024-01-01'"
     limit=4
 Follow-up Query (after verifying results):
     metrics=["new_users"]
     group_by=[{"name": "metric_time", "grain": "WEEK", "type": "time_dimension"}]
-    order_by=[{"name": "metric_time", "descending": false}]
+    order_by=[{"name": "metric_time", "grain": "WEEK", "descending": false}]
     where="{{ TimeDimension('metric_time', 'WEEK') }} >= '2023-01-01' AND {{ TimeDimension('metric_time', 'WEEK') }} < '2024-01-01'"
     limit=null
 </example>

src/dbt_mcp/semantic_layer/client.py

@@ -70,6 +70,25 @@ def default(self, obj):
     return json.dumps(records, indent=2, cls=ExtendedJSONEncoder)
 
 
+# Cap the number of substrings accepted by `list_metrics(search=[...])` so
+# an unbounded LLM-supplied list can't fan out into a burst of parallel
+# GraphQL requests against the Semantic Layer API.
+_MAX_SEARCH_TERMS = 20
+
+
+def _dedupe_metric_items(items: Any) -> list[Any]:
+    """Preserve first-seen order while filtering out duplicate metric names."""
+    seen: set[str] = set()
+    out: list[Any] = []
+    for item in items:
+        name = item.get("name")
+        if name is None or name in seen:
+            continue
+        seen.add(name)
+        out.append(item)
+    return out
+
+
 class SemanticLayerClientProtocol(Protocol):
     def session(self) -> AbstractContextManager[Any]: ...
 
@@ -126,13 +145,55 @@ def __init__(
     async def list_metrics(
         self,
         config: SemanticLayerConfig,
-        search: str | None = None,
+        search: str | list[str] | None = None,
     ) -> ListMetricsResponse:
-        metrics_result = await submit_request(
-            config,
-            {"query": GRAPHQL_QUERIES["metrics"], "variables": {"search": search}},
+        # `search` may be a single substring or a list of substrings; for a list
+        # we fan out one GraphQL call per substring, then merge & dedupe by name.
+        search_terms: list[str | None]
+        if isinstance(search, list):
+            # Strip whitespace, drop empty values, and dedupe identical terms
+            # (preserving first-seen order) so a whitespace-only or duplicated
+            # term can't broaden the fan-out into redundant or no-filter calls.
+            cleaned: list[str] = []
+            seen_terms: set[str] = set()
+            for raw in search:
+                term = raw.strip()
+                if not term or term in seen_terms:
+                    continue
+                seen_terms.add(term)
+                cleaned.append(term)
+            if len(cleaned) > _MAX_SEARCH_TERMS:
+                # Cap the fan-out so a runaway LLM call can't generate an
+                # unbounded burst of parallel GraphQL requests.
+                raise InvalidParameterError(
+                    f"`search` accepts at most {_MAX_SEARCH_TERMS} terms; "
+                    f"got {len(cleaned)}."
+                )
+            search_terms = list(cleaned) if cleaned else [None]
+        else:
+            # Mirror the list-path normalization for parity: a single-string
+            # `search` is stripped, and an empty/whitespace-only string becomes
+            # no filter (search=None).
+            normalized = search.strip() if isinstance(search, str) else search
+            search_terms = [normalized if normalized else None]
+
+        cheap_results = await asyncio.gather(
+            *(
+                submit_request(
+                    config,
+                    {
+                        "query": GRAPHQL_QUERIES["metrics"],
+                        "variables": {"search": term},
+                    },
+                )
+                for term in search_terms
+            )
+        )
+        cheap_items = _dedupe_metric_items(
+            item
+            for r in cheap_results
+            for item in r["data"]["metricsPaginated"]["items"]
         )
-        metrics_count = len(metrics_result["data"]["metricsPaginated"]["items"])
         dimensionless_response = ListMetricsResponse(
             metrics=[
                 MetricToolResponse(
@@ -142,26 +203,39 @@ async def list_metrics(
                     description=m.get("description"),
                     metadata=(m.get("config") or {}).get("meta"),
                 )
-                for m in metrics_result["data"]["metricsPaginated"]["items"]
+                for m in cheap_items
             ]
         )
-        if metrics_count and metrics_count <= config.metrics_related_max:
-            # Re-fetch with the same search filter using a single query that includes
-            # per-metric dimensions and entities. This avoids the N×2 parallel calls
-            # approach: the nested GQL fields return per-metric data accurately (not
-            # an intersection like dimensionsPaginated with multiple metrics would).
+
+        if cheap_items and len(cheap_items) <= config.metrics_related_max:
+            # Re-fetch with per-metric dimensions and entities. Same fan-out:
+            # the nested GQL fields return per-metric data accurately, unlike
+            # dimensionsPaginated with multiple metrics which would intersect.
+            # Fall back to the dimensionless response if the richer query
+            # times out or otherwise fails (one slow term would otherwise
+            # block the whole call via asyncio.gather).
             try:
-                full_result = await submit_request(
-                    config,
-                    {
-                        "query": GRAPHQL_QUERIES["metrics_with_related"],
-                        "variables": {"search": search},
-                    },
-                    timeout=5.0,
+                related_results = await asyncio.gather(
+                    *(
+                        submit_request(
+                            config,
+                            {
+                                "query": GRAPHQL_QUERIES["metrics_with_related"],
+                                "variables": {"search": term},
+                            },
+                            timeout=5.0,
+                        )
+                        for term in search_terms
+                    )
                 )
             except Exception as e:
                 logger.warning(f"Error fetching metrics with related: {e}")
                 return dimensionless_response
+            related_items = _dedupe_metric_items(
+                item
+                for r in related_results
+                for item in r["data"]["metricsPaginated"]["items"]
+            )
             return ListMetricsResponse(
                 metrics=[
                     MetricToolResponse(
@@ -173,7 +247,7 @@ async def list_metrics(
                         dimensions=[d.get("name") for d in (m.get("dimensions") or [])],
                         entities=[e.get("name") for e in (m.get("entities") or [])],
                     )
-                    for m in full_result["data"]["metricsPaginated"]["items"]
+                    for m in related_items
                 ]
             )
         return dimensionless_response
@@ -336,18 +410,19 @@ def _get_order_bys(
         result: list[OrderBySpec] = []
         if order_by is None:
             return result
-        queried_group_by = {g.name: g for g in group_by} if group_by else {}
+        group_by_map = {g.name: g for g in group_by} if group_by else {}
         queried_metrics = set(metrics)
         for o in order_by:
             if o.name in queried_metrics:
                 result.append(OrderByMetric(name=o.name, descending=o.descending))
-            elif o.name in queried_group_by:
-                selected_group_by = queried_group_by[o.name]
+            elif o.name in group_by_map:
                 result.append(
                     OrderByGroupBy(
-                        name=selected_group_by.name,
+                        name=o.name,
                         descending=o.descending,
-                        grain=selected_group_by.grain,
+                        grain=o.grain
+                        if o.grain is not None
+                        else group_by_map[o.name].grain,
                     )
                 )
             else:

src/dbt_mcp/semantic_layer/param_descriptions.py

@@ -8,7 +8,12 @@
 
 SEMANTIC_LAYER_PROJECT_ID = MULTI_PROJECT_PROJECT_ID_DESCRIPTION
 
-SEMANTIC_SEARCH_METRICS = "Filter metrics by substring match against the metric name"
+SEMANTIC_SEARCH_METRICS = (
+    "Filter metrics by substring match against the metric name. "
+    "Accepts either a single substring or a list of substrings; when a list "
+    "is provided, metrics matching any of the substrings are returned "
+    "(deduplicated)."
+)
 
 SEMANTIC_SEARCH_SAVED_QUERIES = (
     "Filter saved queries by substring match on name, label, or description"
@@ -29,8 +34,10 @@
 )
 
 SEMANTIC_ORDER_BY = (
-    "Sort keys; each item has `name` and `descending` (default false); "
-    "order fields should appear in group_by when grouping"
+    "Sort keys; each item has `name`, `descending` (default false), and optional "
+    "`grain` for time dimensions (overrides the grain from group_by; falls back to "
+    "the matching group_by grain when omitted); items may be metric names or "
+    "group_by fields"
 )
 
 SEMANTIC_WHERE = (