What runtime and dependencies are required?
Python 3.8 or higher, plus the packages `httpx`, `fastmcp`, and `pydantic`. A virtual environment is recommended.
@nagarjun226
基本信息
A simple Model Context Protocol (MCP) server that connects Claude AI with the OpenFoodFacts database to create an intelligent nutritional assistant.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"food-tracker-mcp": {
"command": "python",
"args": [
"-m",
"venv",
"venv"
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
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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