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

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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.