Dev Tools
csharp-sdk
The official C# SDK for the Model Context Protocol — build MCP servers and clients in .NET
★ 4.6k starsApache-2.0
View guide →Expose your FastAPI endpoints as Model Context Protocol tools - with authentication - in a few lines of code.
fastapi_mcp is an open-source dev tools project by tadata-org (tadata-org/fastapi_mcp on GitHub). It has 12,019 GitHub stars and 971 forks, is released under the MIT license, and was last updated on GitHub on 24 November 2025.
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.
The official C# SDK for the Model Context Protocol — build MCP servers and clients in .NET
The official Java SDK for building Model Context Protocol servers and clients.
rmcp: the official Rust SDK for the Model Context Protocol — tokio-based servers and clients
Code-search MCP for Claude Code: make your entire codebase the context for any coding agent.
An MCP server plus a CLI tool that indexes local code into a graph database to provide context to AI assistants.
MCP graph engine that compounds context across AI coding assistants.
The most-starred other Dev Tools projects in the LibreAI catalogue — the realistic shortlist if fastapi_mcp is not the right fit.
The open source coding agent
The model-definition framework behind modern AI — thousands of pretrained transformers for text, vision, and audio.
Anthropic's agentic coding tool that lives in your terminal and works across your whole codebase
Cross-platform desktop all-in-one manager for Claude Code, Codex, OpenCode and other coding agents
OpenAI's lightweight coding agent that runs locally in your terminal
Free and open — grab the source, star the repo, and start creating.