Fastapi Mcp
Expose your FastAPI endpoints as Model Context Protocol (MCP) tools, with Auth!
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Built by Tadata
FastAPI-MCP
Expose your FastAPI endpoints as Model Context Protocol (MCP) tools, with Auth!
](https://pypi.org/project/fastapi-mcp/) [ ](#) [ [](https://codecov.io/gh/tadata-org/fastapi_mcp)
Features
- Authentication built in, using your existing FastAPI dependencies!
- FastAPI-native: Not just another OpenAPI -> MCP converter
- Zero/Minimal configuration required - just point it at your FastAPI app and it works
- Preserving schemas of your request models and response models
- Preserve documentation of all your endpoints, just as it is in Swagger
- Flexible deployment - Mount your MCP server to the same app, or deploy separately
- ASGI transport - Uses FastAPI's ASGI interface directly for efficient communication
Hosted Solution
If you prefer a managed hosted solution check out tadata.com.
Installation
We recommend using uv, a fast Python package installer:
uv add fastapi-mcpAlternatively, you can install with pip:
pip install fastapi-mcpBasic Usage
The simplest way to use FastAPI-MCP is to add an MCP server directly to your FastAPI application:
from fastapi import FastAPI
from fastapi_mcp import FastApiMCP
app = FastAPI()
mcp = FastApiMCP(app)
# Mount the MCP server directly to your FastAPI app
mcp.mount()That's it! Your auto-generated MCP server is now available at https://app.base.url/mcp.
Documentation, Examples and Advanced Usage
FastAPI-MCP provides comprehensive documentation. Additionaly, check out the examples directory for code samples demonstrating these features in action.
FastAPI-first Approach
FastAPI-MCP is designed as a native extension of FastAPI, not just a converter that generates MCP tools from your API. This approach offers several key advantages:
- Native dependencies: Secure your MCP endpoints using familiar FastAPI
Depends()for authentication and authorization
- ASGI transport: Communicates directly with your FastAPI app using its ASGI interface, eliminating the need for HTTP calls from the MCP to your API
- Unified infrastructure: Your FastAPI app doesn't need to run separately from the MCP server (though separate deployment is also supported)
This design philosophy ensures minimum friction when adding MCP capabilities to your existing FastAPI services.
Development and Contributing
Thank you for considering contributing to FastAPI-MCP! We encourage the community to post Issues and create Pull Requests.
Before you get started, please see our Contribution Guide.
Community
Don't lose this
Three weeks from now, you'll want Fastapi Mcp again. Will you remember where to find it?
Save it to your library and the next time you need Fastapi Mcp, it’s one tap away — from any AI app you use. Group it into a bench with the rest of the team for that kind of task and you can pull the whole stack at once.
⚡ Pro tip for geeks: add a-gnt 🤵🏻♂️ as a custom connector in Claude or a custom GPT in ChatGPT — one click and your library is right there in the chat. Or, if you’re in an editor, install the a-gnt MCP server and say “use my [bench name]” in Claude Code, Cursor, VS Code, or Windsurf.
a-gnt's Take
Our honest review
This plugs directly into your AI and gives it new abilities it didn't have before. Expose your FastAPI endpoints as Model Context Protocol (MCP) tools, with Auth!. Once connected, just ask your AI to use it. It's completely free and works across most major AI apps. This one just landed in the catalog — worth trying while it's fresh.
Tips for getting started
Tap "Get" above, pick your AI app, and follow the steps. Most installs take under 30 seconds.
What's New
Imported from GitHub
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