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.NET: [Feature Branch] Migrate state schema updates and support for agents as MCP tools (#1979)
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‎dotnet/Directory.Packages.props‎

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<PackageVersion Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask.AzureManaged" Version="1.0.0" />
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<PackageVersion Include="Microsoft.Azure.Functions.Worker.Extensions.Http" Version="3.3.0" />
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<PackageVersion Include="Microsoft.Azure.Functions.Worker.Extensions.Http.AspNetCore" Version="2.1.0" />
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<PackageVersion Include="Microsoft.Azure.Functions.Worker.Extensions.Mcp" Version="1.0.0" />
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<PackageVersion Include="Microsoft.Azure.Functions.Worker.Sdk" Version="2.0.5" />
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<!-- Community -->
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<PackageVersion Include="System.Linq.Async" Version="6.0.3" />

‎dotnet/agent-framework-dotnet.slnx‎

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<Project Path="samples/AzureFunctions/04_AgentOrchestration_Conditionals/04_AgentOrchestration_Conditionals.csproj" />
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<Project Path="samples/AzureFunctions/05_AgentOrchestration_HITL/05_AgentOrchestration_HITL.csproj" />
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<Project Path="samples/AzureFunctions/06_LongRunningTools/06_LongRunningTools.csproj" />
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<Project Path="samples/AzureFunctions/07_AgentAsMcpTool/07_AgentAsMcpTool.csproj" />
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</Folder>
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<Folder Name="/Samples/GettingStarted/">
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<File Path="samples/GettingStarted/README.md" />

‎dotnet/samples/AzureFunctions/01_SingleAgent/host.json‎

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}
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}
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}
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}
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}

‎dotnet/samples/AzureFunctions/07_AgentAsMcpTool/07_AgentAsMcpTool.csproj‎

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<Project Sdk="Microsoft.NET.Sdk">
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<PropertyGroup>
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<TargetFramework>net9.0</TargetFramework>
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<AzureFunctionsVersion>v4</AzureFunctionsVersion>
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<OutputType>Exe</OutputType>
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<ImplicitUsings>enable</ImplicitUsings>
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<Nullable>enable</Nullable>
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<!-- The Functions build tools don't like namespaces that start with a number -->
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<AssemblyName>AgentAsMcpTool</AssemblyName>
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<RootNamespace>AgentAsMcpTool</RootNamespace>
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</PropertyGroup>
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<ItemGroup>
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<FrameworkReference Include="Microsoft.AspNetCore.App" />
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</ItemGroup>
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<!-- Azure Functions packages -->
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<ItemGroup>
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<PackageReference Include="Microsoft.Azure.Functions.Worker" />
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<PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask" />
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<PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask.AzureManaged" />
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<PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.Http.AspNetCore" />
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<PackageReference Include="Microsoft.Azure.Functions.Worker.Sdk" />
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</ItemGroup>
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<ItemGroup>
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<PackageReference Include="Azure.AI.OpenAI" />
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<PackageReference Include="Azure.Identity" />
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</ItemGroup>
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<!-- Local projects that should be switched to package references when using the sample outside of this MAF repo -->
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<!--
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<ItemGroup>
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<PackageReference Include="Microsoft.Agents.AI.Hosting.AzureFunctions" />
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<PackageReference Include="Microsoft.Agents.AI.OpenAI" />
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</ItemGroup>
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-->
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<ItemGroup>
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<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Hosting.AzureFunctions\Microsoft.Agents.AI.Hosting.AzureFunctions.csproj" />
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<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
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</ItemGroup>
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</Project>

‎dotnet/samples/AzureFunctions/07_AgentAsMcpTool/Program.cs‎

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// Copyright (c) Microsoft. All rights reserved.
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// This sample demonstrates how to configure AI agents to be accessible as MCP tools.
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// When using AddAIAgent and enabling MCP tool triggers, the Functions host will automatically
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// generate a remote MCP endpoint for the app at /runtime/webhooks/mcp with a agent-specific
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// query tool name.
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using Azure;
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using Azure.AI.OpenAI;
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using Azure.Identity;
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using Microsoft.Agents.AI;
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using Microsoft.Agents.AI.DurableTask;
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using Microsoft.Agents.AI.Hosting.AzureFunctions;
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using Microsoft.Azure.Functions.Worker.Builder;
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using Microsoft.Extensions.Hosting;
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using OpenAI;
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// Get the Azure OpenAI endpoint and deployment name from environment variables.
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string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT")
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?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
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string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT")
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?? throw new InvalidOperationException("AZURE_OPENAI_DEPLOYMENT is not set.");
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// Use Azure Key Credential if provided, otherwise use Azure CLI Credential.
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string? azureOpenAiKey = Environment.GetEnvironmentVariable("AZURE_OPENAI_KEY");
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AzureOpenAIClient client = !string.IsNullOrEmpty(azureOpenAiKey)
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? new AzureOpenAIClient(new Uri(endpoint), new AzureKeyCredential(azureOpenAiKey))
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: new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential());
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// Define three AI agents we are going to use in this application.
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AIAgent agent1 = client.GetChatClient(deploymentName).CreateAIAgent("You are good at telling jokes.", "Joker");
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AIAgent agent2 = client.GetChatClient(deploymentName)
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.CreateAIAgent("Check stock prices.", "StockAdvisor");
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AIAgent agent3 = client.GetChatClient(deploymentName)
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.CreateAIAgent("Recommend plants.", "PlantAdvisor", description: "Get plant recommendations.");
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using IHost app = FunctionsApplication
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.CreateBuilder(args)
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.ConfigureFunctionsWebApplication()
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.ConfigureDurableAgents(options =>
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{
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options
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.AddAIAgent(agent1) // Enables HTTP trigger by default.
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.AddAIAgent(agent2, enableHttpTrigger: false, enableMcpToolTrigger: true) // Disable HTTP trigger, enable MCP Tool trigger.
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.AddAIAgent(agent3, agentOptions =>
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{
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agentOptions.McpToolTrigger.IsEnabled = true; // Enable MCP Tool trigger.
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});
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})
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.Build();
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app.Run();

‎dotnet/samples/AzureFunctions/07_AgentAsMcpTool/README.md‎

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# Agent as MCP Tool Sample
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This sample demonstrates how to configure AI agents to be accessible as both HTTP endpoints and [Model Context Protocol (MCP)](https://modelcontextprotocol.io/) tools, enabling flexible integration patterns for AI agent consumption.
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## Key Concepts Demonstrated
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- **Multi-trigger Agent Configuration**: Configure agents to support HTTP triggers, MCP tool triggers, or both
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- **Microsoft Agent Framework Integration**: Use the framework to define AI agents with specific roles and capabilities
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- **Flexible Agent Registration**: Register agents with customizable trigger configurations
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- **MCP Server Hosting**: Expose agents as MCP tools for consumption by MCP-compatible clients
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## Sample Architecture
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This sample creates three agents with different trigger configurations:
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| Agent | Role | HTTP Trigger | MCP Tool Trigger | Description |
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|-------|------|--------------|------------------|-------------|
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| **Joker** | Comedy specialist | ✅ Enabled | ❌ Disabled | Accessible only via HTTP requests |
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| **StockAdvisor** | Financial data | ❌ Disabled | ✅ Enabled | Accessible only as MCP tool |
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| **PlantAdvisor** | Indoor plant recommendations | ✅ Enabled | ✅ Enabled | Accessible via both HTTP and MCP |
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## Environment Setup
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See the [README.md](../README.md) file in the parent directory for complete setup instructions, including:
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- Prerequisites installation
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- Azure OpenAI configuration
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- Durable Task Scheduler setup
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- Storage emulator configuration
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For this sample, you'll also need to install [node.js](https://nodejs.org/en/download) in order to use the [MCP Inspector](https://modelcontextprotocol.io/docs/tools/inspector) tool.
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## Configuration
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Update your `local.settings.json` with your Azure OpenAI credentials:
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```json
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{
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"Values": {
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"AZURE_OPENAI_ENDPOINT": "https://your-resource.openai.azure.com/",
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"AZURE_OPENAI_DEPLOYMENT": "your-deployment-name",
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"AZURE_OPENAI_KEY": "your-api-key-if-not-using-rbac"
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}
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}
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```
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## Running the Sample
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1. **Start the Function App**:
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```bash
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cd dotnet/samples/AzureFunctions/07_AgentAsMcpTool
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func start
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```
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2. **Note the MCP Server Endpoint**: When the app starts, you'll see the MCP server endpoint in the terminal output. It will look like:
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```text
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MCP server endpoint: http://localhost:7071/runtime/webhooks/mcp
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```
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## Testing MCP Tool Integration
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Any MCP-compatible client can connect to the server endpoint and utilize the exposed agent tools. The agents will appear as callable tools within the MCP protocol.
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### Using MCP Inspector
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1. Run the [MCP Inspector](https://modelcontextprotocol.io/docs/tools/inspector) from the command line:
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```bash
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npx @modelcontextprotocol/inspector
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```
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1. Connect using the MCP server endpoint from your terminal output
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- For **Transport Type**, select **"Streamable HTTP"**
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- For **URL**, enter the MCP server endpoint `http://localhost:7071/runtime/webhooks/mcp`
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- Click the **Connect** button
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1. Click the **List Tools** button to see the available MCP tools. You should see the `StockAdvisor` and `PlantAdvisor` tools.
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1. Test the available MCP tools:
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- **StockAdvisor** - Set "MSFT ATH" (ATH is "all time high") as the query and click the **Run Tool** button.
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- **PlantAdvisor** - Set "Low light in Seattle" as the query and click the **Run Tool** button.
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You'll see the results of the tool calls in the MCP Inspector interface under the **Tool Results** section. You should also see the results in the terminal where you ran the `func start` command.
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## Learn More
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- [Model Context Protocol Documentation](https://modelcontextprotocol.io/)
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- [Microsoft Agent Framework Documentation](https://github.com/Azure/durable-agent-framework)
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- [Azure Functions Documentation](https://learn.microsoft.com/azure/azure-functions/)

‎dotnet/samples/AzureFunctions/07_AgentAsMcpTool/host.json‎

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{
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"version": "2.0",
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"logging": {
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"logLevel": {
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"Microsoft.Azure.Functions.DurableAgents": "Information",
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"DurableTask": "Information",
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"Microsoft.DurableTask": "Information"
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}
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},
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"extensions": {
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"durableTask": {
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"hubName": "default",
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"storageProvider": {
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"type": "AzureManaged",
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"connectionStringName": "DURABLE_TASK_SCHEDULER_CONNECTION_STRING"
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}
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}
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}
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}

‎dotnet/samples/AzureFunctions/07_AgentAsMcpTool/local.settings.json‎

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{
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"IsEncrypted": false,
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"Values": {
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"FUNCTIONS_WORKER_RUNTIME": "dotnet-isolated",
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"AzureWebJobsStorage": "UseDevelopmentStorage=true",
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"DURABLE_TASK_SCHEDULER_CONNECTION_STRING": "Endpoint=http://localhost:8080;TaskHub=default;Authentication=None",
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"AZURE_OPENAI_ENDPOINT": "<AZURE_OPENAI_ENDPOINT>",
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"AZURE_OPENAI_DEPLOYMENT": "<AZURE_OPENAI_DEPLOYMENT>"
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}
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}

‎dotnet/samples/AzureFunctions/README.md‎

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- **[04_AgentOrchestration_Conditionals](04_AgentOrchestration_Conditionals)**: A sample that demonstrates how to host multiple agents in an Azure Functions app and run them sequentially using a durable orchestration with conditionals.
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- **[05_AgentOrchestration_HITL](05_AgentOrchestration_HITL)**: A sample that demonstrates how to implement a human-in-the-loop workflow using durable orchestration, including external event handling for human approval.
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- **[06_LongRunningTools](06_LongRunningTools)**: A sample that demonstrates how agents can start and interact with durable orchestrations from tool calls to enable long-running tool scenarios.
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- **[07_AgentAsMcpTool](07_AgentAsMcpTool)**: A sample that demonstrates how to configure durable AI agents to be accessible as Model Context Protocol (MCP) tools.
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## Running the Samples
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‎dotnet/src/Microsoft.Agents.AI.DurableTask/AgentEntity.cs‎

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// Copyright (c) Microsoft. All rights reserved.
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using Microsoft.Agents.AI.DurableTask.State;
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using Microsoft.DurableTask.Client;
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using Microsoft.DurableTask.Entities;
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using Microsoft.Extensions.AI;
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logger.LogInformation("Ignoring empty request");
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}
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// TODO: Get state from optional state store
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DurableAgentState state = this.State;
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this.State.Data.ConversationHistory.Add(DurableAgentStateRequest.FromRunRequest(request));
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foreach (ChatMessage msg in request.Messages)
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{
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logger.LogAgentRequest(sessionId, msg.Role, msg.Text);
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state.AddChatMessage(msg);
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}
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// Set the current agent context for the duration of the agent run. This will be exposed
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{
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// Start the agent response stream
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IAsyncEnumerable<AgentRunResponseUpdate> responseStream = agentWrapper.RunStreamingAsync(
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state.EnumerateChatMessages(),
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this.State.Data.ConversationHistory.SelectMany(e => e.Messages).Select(m => m.ToChatMessage()),
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agentWrapper.GetNewThread(),
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options: null,
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this._cancellationToken);
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}
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// Persist the agent response to the entity state for client polling
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state.AddAgentResponse(response, request.CorrelationId);
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this.State.Data.ConversationHistory.Add(
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DurableAgentStateResponse.FromRunResponse(request.CorrelationId, response));
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string responseText = response.Text;
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response.Usage?.TotalTokenCount);
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}
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this.UpdateEntityState(state);
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return response;
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}
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finally
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DurableAgentContext.ClearCurrent();
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}
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}
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private void UpdateEntityState(DurableAgentState state)
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{
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// This method is called to update the state of the entity.
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// It can be used to persist the state to a durable store if needed.
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this.State = state;
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}
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}

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