Entwickler-Tools
csharp-sdk
The official C# SDK for the Model Context Protocol — build MCP servers and clients in .NET
★ 4,6 Tsd. SterneApache-2.0
Anleitung ansehen →fastapi_mcp ist ein Open-Source-Projekt aus der Kategorie Entwickler-Tools von tadata-org (tadata-org/fastapi_mcp auf GitHub). Es hat 12.019 Sterne auf GitHub und 971 Forks, wird unter der Lizenz MIT veröffentlicht und wurde zuletzt am 24. November 2025 auf GitHub aktualisiert.
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.
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.
Die anderen Projekte der Kategorie Entwickler-Tools mit den meisten Sternen im LibreAI-Katalog — die realistische Auswahl, falls fastapi_mcp nicht das Richtige ist.
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
Verwandte Projekte der Kategorie Entwickler-Tools im Katalog, die fastapi_mcp bei den Sternen am nächsten stehen — zum Weiterstöbern auf beiden Seiten.
Code-search MCP for Claude Code: make your entire codebase the context for any coding agent.
ARTEMIS turns natural-language instructions into reliable Android automation. It automates end-to-end workflows, captures logs, and integrates seamlessly wit…
Your AI trading terminal assistant for US stocks, commodities, forex, and crypto.
One Rust CLI for every LLM: shell assistant, chat REPL, RAG, tools and agents across 20+ providers.
All-in-one open-source backend for agentic coding: database, auth, storage, hosting and AI gateway.
A codebase knowledge graph that makes Claude Code, Cursor, Codex and Gemini faster, cheaper and repo-aware.
Kostenlos und offen — hol dir den Quellcode, gib dem Repository einen Stern und leg los.