🚀 FastAPI MCP 服务器

Name: 🚀 FastAPI MCP 服务器
Author: purity3

@purity3

リポジトリ

🚀 FastAPI MCP 服务器について

概要はまだありません

基本情報

カテゴリ

開発者ツール

ライセンス

MIT

ランタイム

python

トランスポート

stdio

公開者

purity3

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "fastapi-mcp-server": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        ".venv"
      ]
    }
  }
}

ツール

ツールは検出されませんでした

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is 🚀 FastAPI MCP 服务器?

The 🚀 FastAPI MCP 服务器 is a lightweight, high-performance implementation of the Model Context Protocol (MCP) for large language models. Built on FastAPI, it provides Server-Sent Events (SSE) communication, intelligent tool registration, and session management for multi-user, multi-model concurrent interactions. It is designed for developers building AI-powered applications that need a standardized backend interface.

How to use 🚀 FastAPI MCP 服务器?

Install Python 3.13+ and optionally uv. Clone the repository, create a virtual environment, and install dependencies with pip install -e .. Configure environment variables in a .env file and create the database file database/session.db. Start the server with python -m main or start. It runs by default on http://localhost:8000. Custom tool functions can be added in the tools/ directory and registered in server.py.

Key features of 🚀 FastAPI MCP 服务器

Integrates FastAPI’s high performance with the MCP protocol
Efficient SSE-based real-time communication with millisecond latency
Multi-user session isolation for data separation
Flexible authentication via token, path, or query parameters
Fully asynchronous architecture supporting high concurrency
Intelligent tool registration system to extend model capabilities

Use cases of 🚀 FastAPI MCP 服务器

Building a custom AI assistant backend with standardized model interactions
Enabling real-time, low-latency tool calls from LLM applications
Developing multi-tenant or multi-user AI-powered services
Creating a pluggable tool ecosystem for model-based workflows

FAQ from 🚀 FastAPI MCP 服务器

How does authentication work?

The server supports multiple authentication methods, including token, path, and query parameters. You can customize the API key verification logic in auth/credential.py.

What are the runtime dependencies?

Python 3.13 or higher is required. An asynchronous database (e.g., SQLite) is optional but recommended for session persistence. The uv package manager is recommended for installation.

Where does session data live?

Session data is stored in database/session.db (SQLite by default). The database file is created manually or automatically on first run. The DATABASE_URL environment variable can be used to configure a different database.

What transport protocol is used?

The server uses Server-Sent Events (SSE) for real-time, unidirectional data streaming from server to client, enabling low-latency communication.

Can I run the server in a container?

Container support is planned for future versions (Docker image and docker-compose). Currently, the server runs directly with Python

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