What are the prerequisites to use this template?
Python 3.10 or higher and `uv` (for environment/package management) are required. The MCP Inspector is recommended for testing, and Git and Docker are optional.
@ltwlf
基本情報
Opinionated starter kit for building Model-Context-Protocol (MCP) server in Python — clean project scaffold, typed code, VS Code debug config, Docker & GitHub Actions ready out-of-the-box
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": {
"python-mcp-starter": {
"command": "uv",
"args": [
"venv"
]
}
}
}ツール一覧はまだありません
この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。
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。
It is a template repository for building Python applications using the Model Context Protocol (MCP) and the MCP Python SDK. It provides a clean, modular architecture for exposing MCP Tools and Resources, along with development tooling, debugging, and Docker support, targeting developers creating MCP servers.
Clone the repository and rename the project package and scripts. Create a virtual environment with uv venv, activate it, then install dependencies with uv pip install -e ".[dev]". Run the server in stdio mode using uv run your-script-name or mcp dev ./your_package_name/server.py, or in SSE mode with uv run your-script-name --sse. Optionally, deploy with Docker via docker-compose up -d.
FastMCP from the Python SDK.uv.Python 3.10 or higher and `uv` (for environment/package management) are required. The MCP Inspector is recommended for testing, and Git and Docker are optional.
In stdio mode, run `uv run your-script-name` (or use the `mcp dev` CLI). For SSE mode, add the `--sse` flag, optionally setting custom host and port with `--host` and `--port`.
Use the `uv run mcp-debug` command, then attach the VS Code debugger with the "Attach to MCP worker" configuration. The template includes debugpy integration. Never enable debug mode in production.
Add tools using the `@mcp.tool()` decorator and resources using the `@mcp.resource()` decorator inside your renamed package’s `server.py` file. The template provides example implementations.
Update the `Dockerfile` and `docker-compose.yml` with your renamed project/package, then run `docker-compose up -d` or build and run directly with `docker build` and `docker run`.

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