How does Meal Server connect to TheMealDB?
It uses TheMealDB’s free API (default key “1”) or a premium key if you have a subscription. The API key is set in the `.env` file.
@D-C2211
基本情報
A server that provides meal-related information through MCP tools
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": {
"mealserver": {
"command": "python",
"args": [
"mealserver.py"
]
}
}
}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。
Meal Server is a Python-based MCP server that provides a convenient interface to TheMealDB API through AI assistants like Claude or Cline. It allows users to search for and retrieve meal recipes, explore categories and cuisines, and create shopping lists using natural language.
Run python mealserver.py from the project directory. Configure environment variables in a .env file (copy from .env.example) to set TheMealDB API key, server host/port, security API key, logging level, and rate limits. Add the server to your MCP client’s settings (e.g., cline_mcp_settings.json) with the command uv --directory <path> run mealserver.py, then restart the client to use tools, resources, and prompts.
It uses TheMealDB’s free API (default key “1”) or a premium key if you have a subscription. The API key is set in the `.env` file.
Meal Server is written in Python and runs via `python mealserver.py`. It uses `uv` to manage the MCP client integration; no other runtime dependencies are mentioned in the README.
Configuration is stored in a local `.env` file in the project root. The `.env` file is excluded from version control via `.gitignore` to protect sensitive information like API keys.
The server uses MCP (Model Context Protocol) for communication with AI clients. It supports an optional API key for server‑to‑client security (set via `MCP_SERVER_API_KEY` in `.env`). Rate limiting (default 60 requests per 60 seconds) is also configurable.
It relies on the free tier of TheMealDB API (default key “1”). Rate limiting can be adjusted via environment variables. The server itself runs locally on the configured host and port (default 127.0.0.1:8080).
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