Overview

This package demonstrates a robust integration between FastAPI and FastMCP, enabling dynamic, modular, and scalable LLM/MCP workflows. It features automatic registration of tools, resources, and prompts for seamless extension.

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Key Features

• FastAPI + FastMCP Integration:

  • Leverages FastMCP.from_fastapi() to expose all FastAPI endpoints as MCP resources/tools via OpenAPI.

• Automatic Discovery & Import:

  • All Python modules in tools/image/, prompts/image/, and resources/ are dynamically imported and registered with MCP at server startup.
  • No manual import maintenance required—just add new modules to the correct folders.

• Type-Checked, Extensible Design:

  • All tools, resources, and prompts use Python type hints for clarity and safety.
  • Modular structure supports rapid extension and testing.

• LLM/Context/Image Support:

  • Tools/resources can use Context for logging, progress, and LLM sampling.
  • Image support for image data workflows.

• Production-Ready

  • Containerized deployment with Docker
  • Async/await support for high concurrency

• ** Secure by Default**

• All communications are secured with SSL/TLS by default. Ensure SSL is enabled in your deployment configuration (e.g., via a reverse proxy like NGINX or an HTTPS-enabled API gateway).-

🚫 Blocked Routes To protect sensitive internal APIs, the following route prefixes are explicitly excluded and inaccessible from the public-facing API:

/system

/service

/mcp_deny

Build and run

docker build -t mcp-server -f app/mcp_server/docker/Dockerfile . docker run -d -p 8000:8000 --name mcp-server mcp-server

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Directory Structure

mcp_server/
├── _docs/                     # Comprehensive documentation
│   ├── concepts/              # Core concepts and architecture
│   ├── examples/              # Usage examples
│   ├── quick-start/           # Getting started guides
│   └── sdk/                   # SDK reference
├── _tests/                    # Test suite
├── context/                   # Context management
│   └── _examples/             # Context usage examples
├── docker/                    # Docker deployment files
│   ├── Dockerfile             # Production Dockerfile
│   └── mcp-server-ssl.conf    # SSL configuration
├── prompts/                   # Prompt templates
│   └── _examples/             # Example prompts
├── resources/                 # MCP resources
│   └── _examples/             # Example resources
├── tools/                     # MCP tools
│   └── _examples/             # Example tools
└── server.py                  # Main MCP server entry point

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Placement: Add to Root of Your App Folder

For MCP to automatically detect and integrate with your FastAPI application, you must place the model_context_protocol directory at the root of your FastAPI app folder (typically where your main FastAPI app module lives, e.g., app/).

• This ensures that server.py can correctly locate and import your FastAPI app (e.g., app.api.main:app).
• If you move the model_context_protocol folder, update the import paths in server.py accordingly.

Example Structure:

app/
├── api/
│   └── main.py    # <-- Your FastAPI app instance (app = FastAPI(...))
├── model_context_protocol/
│   ├── server.py
│   └── ...

Why?

• The MCP server relies on relative imports to dynamically integrate with your FastAPI app.
• Placing model_context_protocol at the app root ensures seamless OpenAPI and MCP integration.

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Getting Started

1. Add this directory (model_context_protocol/) to the root of your FastAPI app folder.
   • This is required for automatic discovery and integration (see directory structure example above).
   • Your FastAPI app instance should be importable as app.api.main:app by default.
2. Install requirements:
   • Python 3.9+
   • fastapi, fastmcp, and all dependencies listed in your environment.
3. Run the MCP server:
   • Use python model_context_protocol/server.py or fastmcp run model_context_protocol/server.py.

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How Integration Works

1. FastAPI + FastMCP

• server.py imports your FastAPI app and passes it to FastMCP.from_fastapi, exposing all FastAPI endpoints as MCP tools/resources.

2. Automatic Module Import

• At startup, server.py uses pkgutil and importlib to dynamically import all modules in:
  • tools/
  • prompts/
  • resources/
• This ensures that any MCP-decorated function (@mcp.tool, @mcp.resource, @mcp.prompt) in these modules is auto-registered with the MCP server.
• To add new functionality: just drop a .py file with MCP-decorated functions into the appropriate folder—no need to edit server.py.

3. Context, Image, and Advanced Features

• Tools/resources can use Context for:
  • Logging (ctx.info, ctx.error)
  • Progress reporting (ctx.report_progress)
  • LLM sampling (ctx.sample)
• Support for Image return types for image workflows.

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Advanced Usage & Features

• For advanced features, integration patterns, and full reproducibility examples, see _docs/context_integration_examples.md.
• Highlights include:
  • LLM Sampling: Use await ctx.sample(...) in tools/resources to request completions from the client LLM.
  • Progress Reporting: Use await ctx.report_progress(current, total) for long-running tasks.
  • Multi-message Prompts: Return a list of UserMessage/AssistantMessage in prompt modules for richer LLM guidance.
  • Dynamic Resources & Pydantic Inputs: See _docs for examples on dynamic resource templates and complex tool schemas.
  • Server Composition/Proxy: See example modules for mounting or proxying other MCP servers.
  • Integration/E2E Testing: Full test scripts and usage instructions are documented in _docs.

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Example: Adding a New Tool

1. Create a new file in tools/tool.py, e.g. resize_tool.py:

   from fastmcp import mcp
   
   @mcp.tool()
   def resize_image(image_path: str, width: int, height: int) -> str:
       """Resize an image and return the new file path."""
       # ... your logic here ...
       return new_path
   

2. Restart your MCP server. The new tool will be auto-registered and available to all MCP clients.

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Contributing

• Follow DRY, SOLID, and clean code principles.
• Use type hints, write tests, and document your tools/resources.

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Credits

• Inspired by The Pragmatic Programmer and The Clean Coder.
• Built by Ty the Programmer Ty The Programmer.

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Requirements

• Python 3.9+
• fastapi, fastmcp, and dependencies installed in your environment.