What runtime and dependencies are required?
Python 3.8 or higher, plus the packages `httpx`, `fastmcp`, and `pydantic`. A virtual environment is recommended.
@nagarjun226
基本情報
A simple Model Context Protocol (MCP) server that connects Claude AI with the OpenFoodFacts database to create an intelligent nutritional assistant.
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": {
"food-tracker-mcp": {
"command": "python",
"args": [
"-m",
"venv",
"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。
Food Tracker MCP is a Model Context Protocol (MCP) server that integrates with the OpenFoodFacts database to track food consumption, analyze nutrition, and manage dietary restrictions. It is designed for users who want to log meals, check products against personal restrictions, and view nutrition summaries.
Install Python 3.8 or higher, create a virtual environment, install dependencies (httpx, fastmcp, pydantic), and run python food_tracker.py. The server exposes tools that can be invoked via Claude after registering the MCP with the Claude platform. Example prompts include scanning barcodes, adding restrictions, logging food, and viewing logs.
Python 3.8 or higher, plus the packages `httpx`, `fastmcp`, and `pydantic`. A virtual environment is recommended.
Data is stored locally in JSON files: user profiles in `./data/users/{user_id}.json` and food logs in `./data/logs/{user_id}_{date}.json`.
Run `python food_tracker.py` in the project directory after installing dependencies. The server will be ready to receive commands.
Yes, because it connects to the OpenFoodFacts API to fetch product information.
Yes, the README suggests adding new nutritional analysis features, diet plans, recipe suggestions, reports, or social features.

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