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<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<TargetFrameworks>net10.0</TargetFrameworks>
<AzureFunctionsVersion>v4</AzureFunctionsVersion>
<OutputType>Exe</OutputType>
<ImplicitUsings>enable</ImplicitUsings>
<Nullable>enable</Nullable>
<!-- The Functions build tools don't like namespaces that start with a number -->
<AssemblyName>AgentAsMcpTool</AssemblyName>
<RootNamespace>AgentAsMcpTool</RootNamespace>
</PropertyGroup>
<ItemGroup>
<FrameworkReference Include="Microsoft.AspNetCore.App" />
</ItemGroup>
<!-- Azure Functions packages -->
<ItemGroup>
<PackageReference Include="Microsoft.Azure.Functions.Worker" />
<PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask" />
<PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask.AzureManaged" />
<PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.Http.AspNetCore" />
<PackageReference Include="Microsoft.Azure.Functions.Worker.Sdk" />
</ItemGroup>
<ItemGroup>
<PackageReference Include="Azure.AI.OpenAI" />
<PackageReference Include="Azure.Identity" />
</ItemGroup>
<!-- Local projects that should be switched to package references when using the sample outside of this MAF repo -->
<!--
<ItemGroup>
<PackageReference Include="Microsoft.Agents.AI.Hosting.AzureFunctions" />
<PackageReference Include="Microsoft.Agents.AI.OpenAI" />
</ItemGroup>
-->
<ItemGroup>
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Hosting.AzureFunctions\Microsoft.Agents.AI.Hosting.AzureFunctions.csproj" />
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
</ItemGroup>
</Project>

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

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# Agent as MCP Tool Sample
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.
## Key Concepts Demonstrated
- **Multi-trigger Agent Configuration**: Configure agents to support HTTP triggers, MCP tool triggers, or both
- **Microsoft Agent Framework Integration**: Use the framework to define AI agents with specific roles and capabilities
- **Flexible Agent Registration**: Register agents with customizable trigger configurations
- **MCP Server Hosting**: Expose agents as MCP tools for consumption by MCP-compatible clients
## Sample Architecture
This sample creates three agents with different trigger configurations:
| Agent | Role | HTTP Trigger | MCP Tool Trigger | Description |
|-------|------|--------------|------------------|-------------|
| **Joker** | Comedy specialist | ✅ Enabled | ❌ Disabled | Accessible only via HTTP requests |
| **StockAdvisor** | Financial data | ❌ Disabled | ✅ Enabled | Accessible only as MCP tool |
| **PlantAdvisor** | Indoor plant recommendations | ✅ Enabled | ✅ Enabled | Accessible via both HTTP and MCP |
## Environment Setup
See the [README.md](../README.md) file in the parent directory for complete setup instructions, including:
- Prerequisites installation
- Azure OpenAI configuration
- Durable Task Scheduler setup
- Storage emulator configuration
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.
## Configuration
Update your `local.settings.json` with your Azure OpenAI credentials:
```json
{
"Values": {
"AZURE_OPENAI_ENDPOINT": "https://your-resource.openai.azure.com/",
"AZURE_OPENAI_DEPLOYMENT": "your-deployment-name",
"AZURE_OPENAI_KEY": "your-api-key-if-not-using-rbac"
}
}
```
## Running the Sample
1. **Start the Function App**:
```bash
cd dotnet/samples/AzureFunctions/07_AgentAsMcpTool
func start
```
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:
```text
MCP server endpoint: http://localhost:7071/runtime/webhooks/mcp
```
## Testing MCP Tool Integration
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.
### Using MCP Inspector
1. Run the [MCP Inspector](https://modelcontextprotocol.io/docs/tools/inspector) from the command line:
```bash
npx @modelcontextprotocol/inspector
```
1. Connect using the MCP server endpoint from your terminal output
- For **Transport Type**, select **"Streamable HTTP"**
- For **URL**, enter the MCP server endpoint `http://localhost:7071/runtime/webhooks/mcp`
- Click the **Connect** button
1. Click the **List Tools** button to see the available MCP tools. You should see the `StockAdvisor` and `PlantAdvisor` tools.
1. Test the available MCP tools:
- **StockAdvisor** - Set "MSFT ATH" (ATH is "all time high") as the query and click the **Run Tool** button.
- **PlantAdvisor** - Set "Low light in Seattle" as the query and click the **Run Tool** button.
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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{
"version": "2.0",
"logging": {
"logLevel": {
"Microsoft.Azure.Functions.DurableAgents": "Information",
"DurableTask": "Information",
"Microsoft.DurableTask": "Information"
}
},
"extensions": {
"durableTask": {
"hubName": "default",
"storageProvider": {
"type": "AzureManaged",
"connectionStringName": "DURABLE_TASK_SCHEDULER_CONNECTION_STRING"
}
}
}
}

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