What is the Model Context Protocol (MCP)?
MCP is a protocol that allows AI models to access external tools and prompts. The template provides an easy way to build an MCP‑compliant server.
@Nisarg38
基本情報
概要はまだありません
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": {
"mcp-server-template-nisarg38": {
"command": "python",
"args": [
"-m",
"src.main"
]
}
}
}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。
A ready‑to‑use template for building Model Context Protocol (MCP) servers in Python. It helps developers quickly create servers that register and expose tools and prompts for AI models to use.
Install with pip install -e ".[dev]" inside a cloned copy of the repository, then start the server with python -m src.main or the mcp-server-template CLI. Command‑line options let you change the port (--port), enable debug mode (--debug), switch transport (--transport stdio), or set the logging level (--log-level).
Dockerfile.MCP is a protocol that allows AI models to access external tools and prompts. The template provides an easy way to build an MCP‑compliant server.
Python 3.10 or newer.
Define a function in `src/main.py` and decorate it with `@mcp.tool()`. The function’s docstring serves as the description shown to the AI.
Build a Docker image with `docker build -t my-mcp-server .` and run it, or deploy the container to any cloud platform that supports containerised apps.
The server supports HTTP (default on port 8080) and stdio. Use `--transport stdio` to switch to the stdio transport.

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