Développement
csharp-sdk
The official C# SDK for the Model Context Protocol — build MCP servers and clients in .NET
★ 4,6 k étoilesApache-2.0
Voir le guide →fastapi_mcp est un projet de développement open source, créé par tadata-org (tadata-org/fastapi_mcp sur GitHub). Il compte 12 019 étoiles sur GitHub et 971 forks, il est publié sous la licence MIT et a été mis à jour pour la dernière fois sur GitHub le 24 novembre 2025.
Expose your FastAPI endpoints as Model Context Protocol tools - with authentication - in a few lines of code.
You need an existing (or new) FastAPI app whose endpoints you want AI agents to call as tools.
Add fastapi-mcp to your project with uv or pip.
Create FastApiMCP(app) in your code and call mcp.mount() - your endpoints become MCP tools with schemas and docs preserved.
Point your MCP client at your app's /mcp endpoint, authenticate as your API requires, and call a tool from your agent.
Secure MCP tools using your existing FastAPI dependencies (Depends) for authentication and authorization - no parallel auth system.
Built as a native extension of FastAPI rather than an OpenAPI translation layer, preserving native dependency behavior.
Request and response models keep their schemas, and endpoint documentation carries over just as it appears in Swagger.
Point it at your FastAPI app and it works - the basic integration is three lines of code.
Mount the MCP server into the same FastAPI app or deploy it separately, as your architecture requires.
The MCP server communicates with your app through its ASGI interface directly, eliminating internal HTTP calls.
Clone FastAPI-MCP for the examples and source; most users install the package instead.
git clone https://github.com/tadata-org/fastapi_mcp.git
cd fastapi_mcpAdd fastapi-mcp to your FastAPI project (uv recommended by the README, pip works too).
pip install fastapi-mcpAdd the MCP server to your FastAPI application; it becomes available at your app's /mcp path.
from fastapi_mcp import FastApiMCP
mcp = FastApiMCP(app)
mcp.mount() # see README for the full exampleIt is developed by tadata-org (Tadata Inc.) and community contributors; Tadata also offers a hosted solution.
Yes. It is MIT-licensed (Copyright Tadata Inc.).
No. It is a library that runs inside your own FastAPI deployment; the AI clients that call it use their own model access.
Generic converters translate the spec; FastAPI-MCP works natively with your running app, reusing its dependencies for auth and its ASGI interface for transport, so behavior matches your API exactly.
Run pip install fastapi-mcp, add FastApiMCP(app) and mcp.mount() to your app, and connect an MCP client to /mcp.
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