Files
Dmytro Struk 67a8147151 .NET: Python: Azure Functions feature branch (#1916)
* Python: Add Scaffolding for Durable AzureFunctions package to Agent Framework (#1823)

* Add scafolding

* update readme

* add code owners and label

* update owners

* .NET: Durable extension: initial src and unit tests (#1900)

* Python: Add Durable Agent Wrapper code (#1913)

* add initial changes

* Move code and add single sample

* Update logger

* Remove unused code

* address PR comments

* cleanup code and address comments

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Co-authored-by: Dmytro Struk <13853051+dmytrostruk@users.noreply.github.com>

* Azure Functions .NET samples (#1939)

* Python: Add Unit tests for Azurefunctions package (#1976)

* Add Unit tests for Azurefunctions

* remove duplicate import

* .NET: [Feature Branch] Migrate state schema updates and support for agents as MCP tools (#1979)

* Python: Add more samples for Azure Functions (#1980)

* Move all samples

* fix comments

* remove dead lines

* Make samples simpler

* .NET: [Feature Branch] Durable Task extension integration tests (#2017)

* .NET: [Feature Branch] Update OpenAI config for integration tests (#2063)

* Python: Add Integration tests for AzureFunctions  (#2020)

* Add Integration tests

* Remove DTS extension

* Apply suggestions from code review

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* Add pyi file for type safety

* Add samples in readme

* Updated all readme instructions

* Address comments

* Update readmes

* Fix requirements

* Address comments

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* .NET: [Feature Branch] Update dotnet-build-and-test.yml to support integration tests (#2070)

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* Fix DTS startup issue and improve logging (#2103)

* .NET: [Feature Branch] Introduce Azure OpenAI config for .NET pipeline (#2106)

Also fixes an issue where we were trying to start docker containers for integration tests on Windows, which doesn't work.

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* Fix uv.lock after merge

* Python: Add README for Azure Functions samples setup (#2100)

* Add README for Azure Functions samples setup

Added setup instructions for Azure Functions samples, including environment setup, virtual environment creation, and running samples.

* Update python/samples/getting_started/azure_functions/README.md

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Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Laveesh Rohra <larohra@microsoft.com>

* Fix or remove broken markdown file links (#2115)

* .NET: [Feature Branch] Update HTTP API to be consistent across languages (#2118)

* Python: Fix AzureFunctions Integration Tests (#2116)

* Add Identity Auth to samples

* Update python/samples/getting_started/azure_functions/README.md

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* Update python/samples/getting_started/azure_functions/01_single_agent/function_app.py

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* Update python/samples/getting_started/azure_functions/02_multi_agent/function_app.py

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* Update python/samples/getting_started/azure_functions/06_multi_agent_orchestration_conditionals/README.md

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* Python: Fix Http Schema (#2112)

* Rename to threadid

* Respond in plain text

* Make snake-case

* Add http prefix

* rename to wait-for-response

* Add query param check

* address comments

* .NET: Remove IsPackable=false in preparation for nuget release (#2142)

* Python: Move `azurefunctions` to `azure` for import (#2141)

* Move import to Azure

* fix mypy

* Update python/packages/azurefunctions/README.md

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* Update python/packages/azurefunctions/pyproject.toml

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* Update python/packages/azurefunctions/agent_framework_azurefunctions/__init__.py

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* Fix imports

* Address PR feedback from westey-m (#2150)

- Adds a link from the /dotnet/samples/README.md to /dotnet/samples/AzureFunctions
- Make DurableAgentThread deserialization internal for future-proofing
- Update JSON serialization logic to address recently discovered issues with source generator serialization

* Address comments (#2160)

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Co-authored-by: Laveesh Rohra <larohra@microsoft.com>
Co-authored-by: Chris Gillum <cgillum@microsoft.com>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Anirudh Garg <anirudhg@microsoft.com>
2025-11-13 02:00:53 +00:00

3.5 KiB

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) 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 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 in order to use the MCP Inspector tool.

Configuration

Update your local.settings.json with your Azure OpenAI credentials:

{
  "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:

    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:

    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 from the command line:

    npx @modelcontextprotocol/inspector
    
  2. 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
  3. Click the List Tools button to see the available MCP tools. You should see the StockAdvisor and PlantAdvisor tools.

  4. 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.