diff --git a/frontend/README.md b/frontend/README.md
index ff19a3e..06f4b8f 100644
--- a/frontend/README.md
+++ b/frontend/README.md
@@ -1,4 +1,78 @@
-# Astro Starter Kit: Basics
+# Gov AI MCP Client - Frontend
+
+A modern AI chat interface that connects to MCP (Model Context Protocol) servers using Vercel AI SDK.
+
+## Features
+
+- **Multiple AI Providers**: Support for Azure OpenAI and Anthropic Claude
+- **MCP Integration**: Native support for Model Context Protocol servers
+- **Streaming Responses**: Real-time streaming of AI responses
+- **Tool Calling**: Seamless integration with external tools and APIs
+- **Modern UI**: Built with Astro and GOV.UK Design System
+
+## Setup
+
+### 1. Install Dependencies
+
+```sh
+npm install
+```
+
+### 2. Environment Configuration
+
+Create a `.env` file in the frontend directory with the following variables:
+
+```env
+# Azure OpenAI Configuration
+AZURE_OPENAI_API_KEY=your_azure_openai_api_key
+AZURE_OPENAI_ENDPOINT=https://your-resource.openai.azure.com
+AZURE_OPENAI_DEPLOYMENT_NAME=your-deployment-name
+
+# Anthropic Configuration  
+ANTHROPIC_API_KEY=your_anthropic_api_key
+
+# Optional: Set default provider (azure or anthropic)
+DEFAULT_AI_PROVIDER=azure
+```
+
+### 3. MCP Server Configuration
+
+Copy `.mcp-servers-example.yaml` to `.mcp-servers.yaml` and configure your MCP servers:
+
+```yaml
+servers:
+  - name: lex
+    description: Research legislation and caselaw
+    url: http://localhost:8000/mcp
+    accessToken: optional_access_token
+```
+
+## 🧞 Commands
+
+| Command                   | Action                                           |
+| :------------------------ | :----------------------------------------------- |
+| `npm install`             | Installs dependencies                            |
+| `npm run dev`             | Starts local dev server at `localhost:4321`      |
+| `npm run build`           | Build your production site to `./dist/`          |
+| `npm run preview`         | Preview your build locally, before deploying     |
+
+## Architecture
+
+This implementation uses **Vercel AI SDK** instead of LangChain for better:
+- **Schema Validation**: More robust handling of OpenAI function calling schemas
+- **MCP Integration**: Native experimental MCP client support
+- **Streaming**: Built-in streaming support with better error handling
+- **Provider Flexibility**: Easy switching between AI providers
+
+## Migration from LangChain
+
+This version replaces the previous LangChain implementation to resolve schema validation issues with OpenAI function calling, particularly around array parameters missing the required `items` property.
+
+Key improvements:
+- Direct MCP client integration via `experimental_createMCPClient`
+- Better error handling and connection management
+- Cleaner streaming implementation
+- Provider-agnostic architecture
 
 ```sh
 npm create astro@latest -- --template basics
@@ -30,19 +104,6 @@ Inside of your Astro project, you'll see the following folders and files:
 
 To learn more about the folder structure of an Astro project, refer to [our guide on project structure](https://docs.astro.build/en/basics/project-structure/).
 
-## 🧞 Commands
-
-All commands are run from the root of the project, from a terminal:
-
-| Command                   | Action                                           |
-| :------------------------ | :----------------------------------------------- |
-| `npm install`             | Installs dependencies                            |
-| `npm run dev`             | Starts local dev server at `localhost:4321`      |
-| `npm run build`           | Build your production site to `./dist/`          |
-| `npm run preview`         | Preview your build locally, before deploying     |
-| `npm run astro ...`       | Run CLI commands like `astro add`, `astro check` |
-| `npm run astro -- --help` | Get help using the Astro CLI                     |
-
-## 👀 Want to learn more?
+## �� Want to learn more?
 
 Feel free to check [our documentation](https://docs.astro.build) or jump into our [Discord server](https://astro.build/chat).
diff --git a/frontend/package-lock.json b/frontend/package-lock.json
index f52e81f..85701a1 100644
--- a/frontend/package-lock.json
+++ b/frontend/package-lock.json
@@ -8,29 +8,146 @@
       "name": "gov-ai-client",
       "version": "0.0.1",
       "dependencies": {
+        "@ai-sdk/anthropic": "^1.0.0",
+        "@ai-sdk/azure": "^1.0.0",
         "@astrojs/node": "^9.2.1",
-        "@langchain/core": "^0.3.55",
-        "@langchain/langgraph": "^0.2.72",
-        "@langchain/mcp-adapters": "^0.4.5",
-        "@langchain/openai": "^0.5.10",
         "@lit-labs/ssr": "^3.3.1",
         "@modelcontextprotocol/sdk": "^1.11.4",
         "@sentry/astro": "^9.33.0",
+        "ai": "^4.0.0",
         "astro": "^5.10.1",
         "dotenv": "^16.4.7",
         "i.ai-design-system": "^0.7.7",
         "jose": "^6.0.10",
-        "langfuse-langchain": "^3.37.4",
         "lit-html": "^3.2.1",
-        "openai": "^4.98.0",
         "showdown": "^2.1.0",
         "tributejs": "^5.1.3",
-        "yaml": "^2.7.1"
+        "yaml": "^2.7.1",
+        "zod": "^3.22.4"
       },
       "devDependencies": {
         "@types/showdown": "^2.0.6"
       }
     },
+    "node_modules/@ai-sdk/anthropic": {
+      "version": "1.2.12",
+      "resolved": "https://registry.npmjs.org/@ai-sdk/anthropic/-/anthropic-1.2.12.tgz",
+      "integrity": "sha512-YSzjlko7JvuiyQFmI9RN1tNZdEiZxc+6xld/0tq/VkJaHpEzGAb1yiNxxvmYVcjvfu/PcvCxAAYXmTYQQ63IHQ==",
+      "license": "Apache-2.0",
+      "dependencies": {
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+        "@ai-sdk/provider-utils": "2.2.8"
+      },
+      "engines": {
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+      },
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+      }
+    },
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+      "license": "Apache-2.0",
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+      "license": "Apache-2.0",
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+        "swr": "^2.2.5",
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+      },
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+      "resolved": "https://registry.npmjs.org/@ai-sdk/ui-utils/-/ui-utils-1.2.11.tgz",
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+      "license": "Apache-2.0",
+      "dependencies": {
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@@ -382,12 +499,6 @@
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@@ -2738,6 +2696,12 @@
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index 4729208..0a5186c 100644
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+    "@ai-sdk/anthropic": "^1.0.0",
+    "ai": "^4.0.0",
     "@lit-labs/ssr": "^3.3.1",
     "@modelcontextprotocol/sdk": "^1.11.4",
     "@sentry/astro": "^9.33.0",
@@ -21,12 +20,11 @@
     "dotenv": "^16.4.7",
     "i.ai-design-system": "^0.7.7",
     "jose": "^6.0.10",
-    "langfuse-langchain": "^3.37.4",
     "lit-html": "^3.2.1",
-    "openai": "^4.98.0",
     "showdown": "^2.1.0",
     "tributejs": "^5.1.3",
-    "yaml": "^2.7.1"
+    "yaml": "^2.7.1",
+    "zod": "^3.22.4"
   },
   "devDependencies": {
     "@types/showdown": "^2.0.6"
diff --git a/frontend/src/components/message-box.mjs b/frontend/src/components/message-box.mjs
index c5005bd..d670bd4 100644
--- a/frontend/src/components/message-box.mjs
+++ b/frontend/src/components/message-box.mjs
@@ -9,7 +9,7 @@ export class MessageBox extends LitElement {
     type: {type: String, attribute: 'type'},
     content: {type: String, attribute: 'content'},
     toolCalls: {type: Array, attribute: 'tool-calls'},
-    streamingInProgress: {type: Boolean, state: true},
+    isStreaming: {type: Boolean, attribute: 'is-streaming'},
     messageIndex: {type: Number, state: true},
   }
 
@@ -27,6 +27,10 @@ export class MessageBox extends LitElement {
      * @type { {name: string, args: []}[] }
      */
     this.toolCalls = this.toolCalls || []
+    /**
+     * @type {boolean}
+     */
+    this.isStreaming = false
   }
 
   createRenderRoot() {
@@ -36,17 +40,27 @@ export class MessageBox extends LitElement {
 
   connectedCallback() {
     super.connectedCallback()
-    if (!this.content && this.type === 'llm') {
-      this.#stream()
-    }
+    
     const messageBoxes = document.querySelectorAll('message-box[type="llm"]')
     messageBoxes.forEach((messageBox, index) => {
       if (messageBox === this) {
-        this.messageIndex = index // should be +1 but we hide the copy button for the intro message
+        this.messageIndex = index
       }
     })
   }
 
+  attributeChangedCallback(name, oldValue, newValue) {
+    super.attributeChangedCallback(name, oldValue, newValue)
+    
+    if (name === 'tool-calls' && newValue) {
+      try {
+        this.toolCalls = JSON.parse(newValue)
+      } catch (e) {
+        console.warn('Error parsing tool calls:', e)
+        this.toolCalls = []
+      }
+    }
+  }
 
   render() {
     return html`
@@ -59,19 +73,15 @@ export class MessageBox extends LitElement {
         ${this.type === 'llm' ? html`
           <h2 class="govuk-visually-hidden">AI:</h2>
           
-          ${this.toolCalls.map(tool => html`
+          ${this.toolCalls && this.toolCalls.length > 0 ? this.toolCalls.map(tool => html`
             <tool-info name=${tool.name} entries=${JSON.stringify(tool.args)}></tool-info>
-          `)}
+          `) : nothing}
 
           ${this.content ? html`
             <markdown-converter id=${'message-' + this.messageIndex} class="govuk-body" content=${this.content}></markdown-converter>
           ` : nothing}
 
-          ${this.streamingInProgress ? html`
-            <loading-message></loading-message>
-          ` : nothing}
-
-          ${!this.streamingInProgress ? html`
+          ${!this.isStreaming && this.content ? html`
             <copy-button class="govuk-!-margin-top-2" copy=${'message-' + this.messageIndex}>
               Copy
               <span class="govuk-visually-hidden">response ${this.messageIndex}</span>
@@ -84,65 +94,6 @@ export class MessageBox extends LitElement {
     `
   }
 
-
-  #stream() {
-
-    this.streamingInProgress = true
-
-    window.setTimeout(() => {
-      /** @type { HTMLElement | null } */
-      const messageBox = this.querySelector('.message-box');
-      messageBox?.focus()
-    }, 100);
-    
-    // get message in view
-    window.setTimeout(() => {
-      this.scrollIntoView({
-        block: 'start',
-        behavior: 'instant'
-      })
-    }, 100);
-    /** @type {HTMLElement | null} */(this.querySelector('.message-box'))?.focus()
-
-    // setup SSE
-    const source = new EventSource('/api/sse')
-    source.onmessage = (evt) => {
-      
-      // parse response data
-      /**
-       * @type { {type?: 'tool' | 'content' | 'end', data?: any} }
-       */
-      let response = {}
-      try {
-        response = JSON.parse(evt.data)
-      } catch (err) {
-        console.log(err)
-        return
-      }
-
-      // It's a tool
-      if (response.type === 'tool') {
-        this.toolCalls = [...this.toolCalls, response.data[0]]
-
-      // It's the text response
-      } else if (response.type === 'content') {        
-        this.content += response.data
-
-      } else if (response.type === 'end') {
-        source.close()
-        this.streamingInProgress = false
-      }
-
-    }
-    source.onerror = (err) => {
-      console.log('SSE error:', err)
-      source.close()
-      this.streamingInProgress = false
-      window.setTimeout(this.#stream, 500)
-    }
-    
-  }
-
 }
 
 customElements.define("message-box", MessageBox)
diff --git a/frontend/src/components/tools.astro b/frontend/src/components/tools.astro
index d6b2810..9e8c223 100644
--- a/frontend/src/components/tools.astro
+++ b/frontend/src/components/tools.astro
@@ -1,19 +1,8 @@
 ---
 import { mcpServers } from '../logic/get-servers.ts';
-import { getTools, type Tool } from '../logic/get-tools.ts';
-
-
-const { mcpTools, serversWithFailedConnections } = await getTools(mcpServers, Astro.request.headers.get('x-amzn-oidc-accesstoken') || '');
-
-// create toolList to make it easier to reference tools for a particular server in the template
-let toolList: { [toolName: string]: Tool[] } = {};
-mcpTools.forEach((tool) => {
-  if (!toolList[tool.serverName]) {
-    toolList[tool.serverName] = [];
-  }
-  toolList[tool.serverName].push(tool);
-});
 
+// With the new AI SDK approach, we handle MCP connections at runtime
+// So we just show the available servers without pre-fetching tools
 ---
 
 { mcpServers.map((server) =>
@@ -21,50 +10,20 @@ mcpTools.forEach((tool) => {
     <input class={ 'govuk-checkboxes__input plausible-event-name=Plugin+Click plausible-event-plugin=' + server.name } id={ 'tool-' + server.name } name="servers" type="checkbox" value={ server.name } aria-describedby={'tool-hint-' + server.name } />
     <label class="govuk-label govuk-checkboxes__label govuk-!-padding-right-0" for={ 'tool-' + server.name }>
       <span class="govuk-body-s">{ server.name }</span>
-      { serversWithFailedConnections.includes(server.name) && 
-        <strong class="govuk-tag govuk-tag--red govuk-!-padding-left-1 govuk-!-padding-right-1 govuk-!-padding-top-0"><span class="govuk-body-xs">Error</span></strong>
-      }
-      { !serversWithFailedConnections.includes(server.name) && toolList[server.name]?.length === 0 &&
-        <strong class="govuk-tag govuk-tag--red govuk-!-padding-left-1 govuk-!-padding-right-1 govuk-!-padding-top-0"><span class="govuk-body-xs">No tools found</span></strong>
-      }
     </label>
-    { !serversWithFailedConnections.includes(server.name) && toolList[server.name]?.length > 0 &&
-      <div id={'tool-hint-' + server.name } class="tool-selector__tools govuk-hint govuk-checkboxes__hint govuk-!-margin-top-1 govuk-!-padding-0" style="font-size: 1rem;">
-        <details class="govuk-details govuk-!-margin-bottom-0">
-          <summary class={ 'govuk-details__summary plausible-event-name=Expand+Tool+List plausible-event-plugin=' + server.name }>
-            <span class="govuk-details__summary-text govuk-body-xs govuk-!-font-weight-bold">Tools</span><span class="govuk-body-xs"> ({ toolList[server.name].length })</span>
-          </summary>
-          <div class="govuk-details__text">
-            <ul class="govuk-list govuk-!-margin-bottom-0">
-              { toolList[server.name].map((tool) =>
-                <li class="govuk-body-xs govuk-!-margin-top-2">
-                  <strong class="govuk-!-display-block js-tool">{ tool.name }:</strong>
-                  { tool.description }
-                </li>
-              )}
-            </ul>
-          </div>
-        </details>
-      </div>
-    }
+    <div id={'tool-hint-' + server.name } class="tool-selector__tools govuk-hint govuk-checkboxes__hint govuk-!-margin-top-1 govuk-!-padding-0" style="font-size: 1rem;">
+      <span class="govuk-body-xs" style="color: #505a5f;">{ server.description }</span>
+    </div>
   </div>
 )}
 
 
 <style>
   .tool-selector__tools {
-    summary::before {
-      color: #505a5f;
-      left: 3px;
-    };
-    summary span {
+    span {
       color: #505a5f;
       position: relative; top: -2px;
     }
-    li {
-      color: #505a5f;
-      word-wrap: break-word;
-    }
   }
   .tool-selector__exclamation {
     align-items: center;
diff --git a/frontend/src/logic/ai-sdk.ts b/frontend/src/logic/ai-sdk.ts
new file mode 100644
index 0000000..09276ea
--- /dev/null
+++ b/frontend/src/logic/ai-sdk.ts
@@ -0,0 +1,180 @@
+// Using Vercel AI SDK for MCP and LLM calls
+// Replaces ai3.ts LangChain implementation
+
+import 'dotenv/config'
+
+import { createAzure } from '@ai-sdk/azure'
+import { createAnthropic } from '@ai-sdk/anthropic'
+import { experimental_createMCPClient as createMCPClient, streamText } from 'ai'
+import { mcpServers } from './get-servers.ts'
+import { StreamableHTTPClientTransport } from '@modelcontextprotocol/sdk/client/streamableHttp';
+
+
+export type Message = {
+  type: 'user' | 'llm'
+  response: {
+    content: string,
+    tools?: {}[],
+    tool_calls: [],
+  }
+}
+
+type Provider = 'azure' | 'anthropic'
+
+export const getLlmResponse = async (
+  messages: Message[], 
+  selectedServers: string[], 
+  authToken: string,
+  provider: Provider = 'azure',
+) => {
+
+  // Create model based on provider
+  const azure = createAzure({
+    resourceName: process.env.AZURE_OPENAI_ENDPOINT?.replace('https://', '').replace('.openai.azure.com/', ''),
+    apiKey: process.env.AZURE_OPENAI_API_KEY,
+  })
+  
+  const anthropicClient = createAnthropic({
+    apiKey: process.env.ANTHROPIC_API_KEY,
+  })
+
+  const model = provider === 'azure' 
+    ? azure(process.env.AZURE_OPENAI_DEPLOYMENT_NAME || 'o4-mini')
+    : anthropicClient('claude-3-5-sonnet-20241022');
+
+  // Filter out any unselected MCP servers
+  const selectedMcpServers = mcpServers.filter((server: {name: string}) => selectedServers.includes(server.name));
+
+  // Create MCP clients for selected servers
+  const mcpClients: any[] = []
+  let allTools = {}
+
+  for (const server of selectedMcpServers) {
+    try {
+      const headers: Record<string, string> = {}
+      
+      if (server.accessToken) {
+        headers['x-external-access-token'] = server.accessToken
+      }
+      if (authToken) {
+        headers['x_amzn_oidc_accesstoken'] = authToken
+        headers['Authorization'] = `Bearer ${authToken}`
+      }
+
+      const transportType = (server.url.includes('/sse') || server.transportType === 'sse') ? 'sse' : 'streamable';
+      let client;
+
+      if (transportType === 'sse') {
+
+        client = await createMCPClient({
+          transport: {
+            type: 'sse',
+            url: server.url,
+            headers,
+          }
+        });
+
+      } else {
+
+        const transportOptions = {
+          eventSourceInit: {
+            fetch: (input: string, init: {}) =>
+              fetch(input, {
+                ...init,
+                headers,
+              }),
+          },
+          requestInit: {
+            headers,
+          }
+        };
+
+        client = await createMCPClient({
+          transport: new StreamableHTTPClientTransport(new URL(server.url), transportOptions)
+        });
+      
+      }
+      
+      const tools = await client.tools()
+      allTools = { ...allTools, ...tools }
+      mcpClients.push(client)
+      
+      console.log(`${server.name}: Connected using ${transportType}`)
+    } catch (error) {
+      console.log(`${server.name}: Error connecting to MCP server`, error)
+    }
+  }
+
+  const currentTime = new Date().toLocaleString('en-GB', {
+    day:     'numeric',
+    month:   'short',
+    year:    'numeric',
+    hour:    'numeric',
+    minute:  '2-digit',
+    hour12:  true
+  });
+
+  let systemMessageText: string = `
+    You are a UK civil servant. The current time is ${currentTime}.
+    If you see a word starting with "@" search for a tool by that name and use it. 
+    Where appropriate cite any responses from tools to support answer, e.g. provide:
+    - source, i.e. link or title (this should be verbatim, do not modify, or invent this. Use concise but descriptive names for links so each unique link text describes the destination. Ensure all links are rendered as proper markdown links)
+    - quotes
+    - etc
+    Reply in British English.
+    Use semantic markdown in your response, but do not display anything as footnotes.
+  `;
+  if (selectedMcpServers.length) {
+    systemMessageText += 'You should call an MCP tool if one is available.';
+  }
+
+  // Convert messages to AI SDK format
+  const aiMessages = messages.map(message => ({
+    role: message.type === 'user' ? 'user' as const : 'assistant' as const,
+    content: message.response.content
+  }))
+
+  try {
+    // Stream the response using the correct AI SDK pattern
+    const result = streamText({
+      model: model,
+      messages: aiMessages,
+      tools: allTools,
+      maxSteps: 5,
+      system: systemMessageText,
+      onChunk: (chunk) => {
+        console.log(chunk);
+      },
+      onFinish: async () => {
+        // Clean up MCP clients when done
+        await Promise.all(mcpClients.map(async (client) => {
+          try {
+            await client.close()
+          } catch (error) {
+            console.warn('Error closing MCP client:', error)
+          }
+        }))
+      },
+      onError: (err) => {
+        console.log(err);
+      }
+    })
+
+    return result
+
+  } catch (err) {
+    console.error('Error connecting to LLM. Check your env vars.')
+    console.log(err)
+    
+    // Clean up MCP clients on error
+    await Promise.all(mcpClients.map(async (client) => {
+      try {
+        await client.close()
+      } catch (error) {
+        console.warn('Error closing MCP client:', error)
+      }
+    }))
+    
+    throw err
+  }
+} 
\ No newline at end of file
diff --git a/frontend/src/logic/ai3.ts b/frontend/src/logic/ai3.ts
deleted file mode 100644
index b3426c9..0000000
--- a/frontend/src/logic/ai3.ts
+++ /dev/null
@@ -1,147 +0,0 @@
-// Using Langchain for the MCP and LLM calls
-// Same as ai2.ts but uses streaming
-
-import 'dotenv/config'
-
-import { createReactAgent } from '@langchain/langgraph/prebuilt'
-import { AzureChatOpenAI } from '@langchain/openai'
-import { AIMessage, HumanMessage, SystemMessage } from '@langchain/core/messages'
-import { sendMessage } from '../pages/api/sse'
-import { mcpServers } from './get-servers.ts'
-import { getTools } from './get-tools.ts'
-import { CallbackManager } from '@langchain/core/callbacks/manager'
-import { CallbackHandler as LangfuseHandler } from "langfuse-langchain"
-
-
-const langfuseHandler = new LangfuseHandler({
-  secretKey: process.env.LANGFUSE_SECRET_KEY,
-  publicKey: process.env.LANGFUSE_PUBLIC_KEY,
-  baseUrl: 'https://cloud.langfuse.com',
-})
-const callbackManager = CallbackManager.fromHandlers(langfuseHandler)
-
-
-export type Message = {
-  type: 'user' | 'llm'
-  response: {
-    content: string,
-    tools?: {}[],
-    tool_calls: [],
-  }
-}
-
-
-export const getLlmResponse = async (messages: Message[], selectedServers: string[], authToken: string) => {
-
-  const agentModel = new AzureChatOpenAI({
-    openAIApiKey: process.env['AZURE_OPENAI_API_KEY'],
-    openAIApiVersion: process.env['OPENAI_API_VERSION'],
-    openAIBasePath: process.env['AZURE_OPENAI_ENDPOINT'],
-    deploymentName: 'o4-mini',
-    callbackManager,
-  });
-
-  // filter out any unselected MCP servers
-  const selectedMcpServers = mcpServers.filter((server: {name: string}) => selectedServers.includes(server.name));
-
-  // Get mcpTools for all servers
-  const { mcpTools } = await getTools(selectedMcpServers, authToken);
-
-  let agent = createReactAgent({
-    llm: agentModel,
-    tools: mcpTools
-  });
-
-  let systemMessageText: string = `
-    You are a UK civil servant. 
-    If you see a word starting with "@" search for a tool by that name and use it. 
-    Where appropriate cite any responses from tools to support answer, e.g. provide:
-    - source, i.e. link or title (this should be verbatim, do not modify, or invent this. Use concise but descriptive names for links so each unique link text describes the destination. Ensure all links are rendered as proper markdown links)
-    - quotes
-    - etc
-    Reply in British English.
-    Use semantic markdown in your response, but do not display anything as footnotes.
-  `;
-  if (selectedMcpServers.length) {
-    systemMessageText += 'You should call an MCP tool if one is available.';
-  }
-
-  let agentMessages: (HumanMessage | AIMessage)[] = [
-    new SystemMessage(systemMessageText)
-  ]
-  messages.forEach((message) => {
-    if (message.type === 'user') {
-      agentMessages.push(new HumanMessage(message.response.content))
-    } else if (message.type === 'llm') {
-      agentMessages.push(new AIMessage(message.response.content))
-    }
-  });
-
-  // Set up streaming
-  let finalMessage: string = ''
-  let toolCalls: {}[] = []
-  agent.streamMode = ['messages', 'updates']
-  
-  let agentStream;
-  try {
-    agentStream = await agent.stream(
-      { messages: agentMessages },
-      { callbacks: [langfuseHandler] },
-    )
-  } catch (err) {
-    console.error('Error connecting to LLM. Check your env vars.')
-    console.log(err)
-    const msg = 'There is a problem connecting to the LLM. Please try again.'
-    sendMessage(JSON.stringify({
-      type: 'content',
-      data: msg
-    }))
-    sendMessage(JSON.stringify({
-      type: 'end'
-    }))
-    return {
-      content: msg
-    }
-  }
-
-  for await (const chunk of agentStream) {
-
-    // 'messages' stream
-    if (chunk[0] && chunk[0].content && !chunk[0].tool_call_id) {
-      // tool_call_id shows the response from the tool (in case we want it in future)
-      sendMessage(JSON.stringify({
-        type: 'content',
-        data: chunk[0].content
-      }))
-    }
-
-    // 'updates' stream
-    if (!chunk.length) {
-      const response = chunk.agent?.messages ? chunk.agent.messages[0] : {};
-      if (response.tool_calls?.length) {
-        const toolCall = response.tool_calls.map((tool: {name: string, args: {request?: string}}) => {
-          return {
-            name: tool.name,
-            args: tool.args.request || tool.args
-          }
-        })
-        toolCalls.push(...toolCall)
-        sendMessage(JSON.stringify({
-          type: 'tool',
-          data: toolCall
-        }))
-      } else if (response.content) {
-        finalMessage = response.content
-        sendMessage(JSON.stringify({
-          type: 'end'
-        }))
-      }
-    }
-  }
-
-  return {
-    content: finalMessage,
-    tool_calls: toolCalls
-  }
-
-}
diff --git a/frontend/src/logic/get-servers.ts b/frontend/src/logic/get-servers.ts
index ed495dd..d7b2146 100644
--- a/frontend/src/logic/get-servers.ts
+++ b/frontend/src/logic/get-servers.ts
@@ -9,6 +9,7 @@ export type MCP_SERVER = {
   description?: string,
   url: string,
   accessToken?: string,
+  transportType?: 'sse' | 'streamable',
 }
 
 
diff --git a/frontend/src/logic/get-tools.ts b/frontend/src/logic/get-tools.ts
deleted file mode 100644
index d4c328a..0000000
--- a/frontend/src/logic/get-tools.ts
+++ /dev/null
@@ -1,77 +0,0 @@
-import { Client } from '@modelcontextprotocol/sdk/client/index.js';
-import { SSEClientTransport, type SSEClientTransportOptions } from '@modelcontextprotocol/sdk/client/sse.js';
-import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp.js";
-import { loadMcpTools } from '@langchain/mcp-adapters';
-import type { MCP_SERVER } from './get-servers';
-import type { StructuredToolInterface } from '@langchain/core/tools';
-import type { ToolInputSchemaBase } from '@langchain/core/dist/tools/types';
-
-
-export type Tool = StructuredToolInterface<
-  ToolInputSchemaBase,
-  any,
-  any
-> & {
-  serverName: string
-}
-
-
-export const getTools = async (servers: MCP_SERVER[], authToken: string ) => {
-
-  let mcpTools: Tool[] = [];
-  let serversWithFailedConnections = [];
-
-  for (const mcpServer of servers) {
-    const serverHeaders: any = {};
-    if (mcpServer.accessToken) {
-      serverHeaders['x-external-access-token'] = mcpServer.accessToken;
-    }
-    if (authToken) {
-      serverHeaders['x_amzn_oidc_accesstoken'] = authToken;
-      serverHeaders['Authorization'] = `Bearer ${authToken}`;
-    }
-    const transportOptions = {
-      eventSourceInit: {
-        fetch: (input: string, init: {}) =>
-          fetch(input, {
-            ...init,
-            headers: serverHeaders
-          }),
-      },
-      requestInit: {
-        headers: serverHeaders
-      }
-    };
-    try {
-      const client = new Client({
-          name: mcpServer.name,
-          version: "1.0.0"
-        });
-      try {
-        const transport: StreamableHTTPClientTransport = new StreamableHTTPClientTransport(new URL(mcpServer.url), transportOptions);
-        await client.connect(transport);
-        console.log(`${mcpServer.name}: Connected using Streamable HTTP transport`);
-      } catch (error) {
-        //console.log(`${mcpServer.name}: Streamable HTTP connection failed, falling back to SSE transport`);
-        const sseTransport = new SSEClientTransport(new URL(mcpServer.url), transportOptions as SSEClientTransportOptions);
-        await client.connect(sseTransport, {
-          timeout: 2000,
-        });
-        console.log(`${mcpServer.name}: Connected using SSE transport`);
-      }
-
-      const serverMcpTools = (await loadMcpTools(mcpServer.url, client) as Tool[]);
-      serverMcpTools.forEach((tool) => {
-        tool.serverName = mcpServer.name;
-      });
-
-      mcpTools.push(...serverMcpTools);
-    } catch (error) {
-      console.log(`${mcpServer.name}: Error trying to access this server`, error);
-      serversWithFailedConnections.push(mcpServer.name);
-    }
-  }
-
-  return { mcpTools, serversWithFailedConnections };
-
-};
diff --git a/frontend/src/pages/index.astro b/frontend/src/pages/index.astro
index aa033fa..97d9b06 100644
--- a/frontend/src/pages/index.astro
+++ b/frontend/src/pages/index.astro
@@ -2,7 +2,7 @@
 import Layout from '../layouts/Layout.astro';
 import Tools from '../components/tools.astro';
 import LitWrapper from '../components/lit-wrapper.astro';
-import type { Message } from '../logic/ai3.ts';
+import type { Message } from '../logic/ai-sdk.ts';
 
 
 let messages: Message[] | undefined = await Astro.session?.get('messages');
@@ -56,6 +56,7 @@ let messages: Message[] | undefined = await Astro.session?.get('messages');
             <button class="govuk-button govuk-!-margin-bottom-0 plausible-event-name=Send+Prompt">Send</button>
             <a class="govuk-link govuk-!-font-size-16 govuk-!-margin-bottom-0 plausible-event-name=New+Chat" href="/clear-session">Start a new chat</a>
           </div>
+
         </div>
 
       </div>
@@ -71,6 +72,17 @@ let messages: Message[] | undefined = await Astro.session?.get('messages');
               <div class="govuk-checkboxes govuk-checkboxes--small govuk-checkboxes" data-module="govuk-checkboxes">
                 <Tools />
               </div>
+
+              {/*
+              <div class="govuk-form-group govuk-!-margin-top-4">
+                <label class="govuk-label govuk-label--s" for="provider">AI Provider</label>
+                <select class="govuk-select" id="provider" name="provider">
+                  <option value="azure">Azure OpenAI</option>
+                  <option value="anthropic">Anthropic Claude</option>
+                </select>
+              </div>
+               */}
+
             </fieldset>
           </div>
         </tool-selector>
@@ -87,33 +99,127 @@ let messages: Message[] | undefined = await Astro.session?.get('messages');
 
     const textArea = document.querySelector('message-input') as MessageInput;
     const form = document.querySelector('form') as HTMLFormElement
+    const providerSelect = document.querySelector('#provider') as HTMLSelectElement | null;
     let container = document.querySelector('#message-container') as HTMLElement
-    form.addEventListener('submit', (evt) => {
+    
+    // Store messages in memory for the session
+    let sessionMessages: Array<{type: 'user' | 'llm', response: {content: string, tool_calls: any[]}}> = []
+    
+    form.addEventListener('submit', async (evt) => {
       evt.preventDefault()
 
-      const formData = new URLSearchParams(new FormData(form) as unknown as string[][]).toString()
-
-      // set up new message
+      const formData = new FormData(form)
+      const userPrompt = textArea.getValue()
+      const selectedServers = formData.getAll('servers')
+      const provider = providerSelect?.value
+
+      // Add user message to session
+      const userMessage = {
+        type: 'user' as const,
+        response: {
+          content: userPrompt,
+          tool_calls: []
+        }
+      }
+      sessionMessages.push(userMessage)
+
+      // set up new message elements
       let messageBoxUser = document.createElement('message-box')
       messageBoxUser.setAttribute('type', 'user')
-      messageBoxUser.setAttribute('content', textArea.getValue().replace(/"/g, '&quot;'))
+      messageBoxUser.setAttribute('content', userPrompt.replace(/"/g, '&quot;'))
       container.appendChild(messageBoxUser)
 
       let messageBoxLLM = document.createElement('message-box')
       messageBoxLLM.setAttribute('type', 'llm')
       container.appendChild(messageBoxLLM)
       
-      // send prompt
-      fetch("/post-message", {
-        method: "POST",
-        headers: {
-            'Content-Type': 'application/x-www-form-urlencoded',
-        },
-        body: formData
-      });
+      // Send the request and handle streaming response
+      try {
+        const response = await fetch("/post-message", {
+          method: "POST",
+          headers: {
+            'Content-Type': 'application/json',
+          },
+          body: JSON.stringify({
+            messages: sessionMessages,
+            selectedServers,
+            authToken: null, // Will be set by middleware if needed
+            provider
+          })
+        })
+
+        if (!response.ok) {
+          throw new Error(`HTTP error! status: ${response.status}`)
+        }
+
+        // Handle AI SDK data stream protocol
+        const reader = response.body?.getReader()
+        const decoder = new TextDecoder()
+        let llmContent = ''
+        let toolCalls: any[] = []
+
+        if (reader) {
+          while (true) {
+            const { done, value } = await reader.read()
+            if (done) {
+              // Stream is complete
+              break
+            }
+
+            const chunk = decoder.decode(value, { stream: true })
+            const lines = chunk.split('\n').filter(line => line.trim())
+
+            for (const line of lines) {
+              console.log('Stream line:', line) // Debug log
+              if (line.startsWith('0:')) {
+                // Text content from AI SDK (format: 0:"text content")
+                try {
+                  const content = JSON.parse(line.substring(2))
+                  if (content) {
+                    llmContent += content
+                    messageBoxLLM.setAttribute('content', llmContent)
+                  }
+                } catch (e) {
+                  console.warn('Error parsing text content:', e)
+                }
+              } else if (line.startsWith('9:')) {
+                // Tool call part (format: 9:{"toolCallId":"call-123","toolName":"my-tool","args":{"some":"argument"}})
+                try {
+                  const data = JSON.parse(line.substring(2))
+                  if (data.toolCallId && data.toolName) {
+                    toolCalls.push({
+                      name: data.toolName,
+                      args: data.args
+                    })
+                    messageBoxLLM.setAttribute('tool-calls', JSON.stringify(toolCalls))
+                  }
+                } catch (e) {
+                  console.warn('Error parsing tool call data:', e)
+                }
+              } else if (line.startsWith('d:')) {
+                // Stream finished (format: d:{"finishReason":"stop","usage":{"promptTokens":10,"completionTokens":20}})
+                console.log('Stream finished detected!') // Debug log
+                break
+              }
+            }
+          }
+        }
+
+        // Add LLM response to session
+        sessionMessages.push({
+          type: 'llm',
+          response: {
+            content: llmContent,
+            tool_calls: toolCalls
+          }
+        })
+
+      } catch (error) {
+        console.error('Error sending message:', error)
+        messageBoxLLM.setAttribute('content', 'Sorry, there was an error processing your request.')
+      }
 
       textArea.reset()
-
     })
 
   </script>
diff --git a/frontend/src/pages/post-message.ts b/frontend/src/pages/post-message.ts
index 263c92b..6c51875 100644
--- a/frontend/src/pages/post-message.ts
+++ b/frontend/src/pages/post-message.ts
@@ -1,49 +1,24 @@
-import { getLlmResponse } from '../logic/ai3.ts'
-import type { Message } from '../logic/ai3.ts'
+import type { APIRoute } from 'astro'
+import { getLlmResponse } from '../logic/ai-sdk'
 
-export async function POST({ request, redirect, session }) {
-
-  // get user prompt and selected MCP servers
-  let userPrompt = '';
-  let selectedServers = [];
+export const POST: APIRoute = async ({ request }) => {
   try {
-    const data = await request.formData()
-    userPrompt = data.get('prompt')?.toString() || '';
-    selectedServers = data.getAll('servers');
-  } catch (error) {
-    if (error instanceof Error) {
-      console.error(error.message)
-    }
-  }
-
-  // add user prompt to session data
-  let messages: Message[] | undefined = await session?.get('messages')
-  if (!messages) {
-    messages = []
-  }
-  if (userPrompt) {
-    messages.push({
-      type: 'user', response: {
-        content: userPrompt
-      }
-    })
-  }
+    const body = await request.json()
+    console.log('Request body:', body) // Debug log
+    
+    const { messages, selectedServers, authToken, provider } = body
 
-  // get LLM response
-  let llmResponse;
-  if (userPrompt) {
-    llmResponse = await getLlmResponse(messages, selectedServers, request.headers.get('x-amzn-oidc-accesstoken'))
-  }
+    if (!messages || !Array.isArray(messages)) {
+      console.error('Invalid messages format:', messages)
+      return new Response('Invalid messages format', { status: 400 })
+    }
 
-  // add LLM response to session data
-  if (llmResponse) {
-    messages.push({
-      type: 'llm', response: llmResponse
-    })
+    const result = await getLlmResponse(messages, selectedServers || [], authToken, provider)
+    
+    // Return the streaming response directly
+    return result.toDataStreamResponse()
+  } catch (error) {
+    console.error('Error in post-message:', error)
+    return new Response(`Internal server error: ${error instanceof Error ? error.message : String(error)}`, { status: 500 })
   }
-
-  // save session data
-  await session?.set('messages', messages)
-
-  return redirect('/')
 }