Food Tracker MCP
@nagarjun226
About Food Tracker MCP
A simple Model Context Protocol (MCP) server that connects Claude AI with the OpenFoodFacts database to create an intelligent nutritional assistant.
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"food-tracker-mcp": {
"command": "python",
"args": [
"-m",
"venv",
"venv"
]
}
}
}Tools
No tools detected
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Overview
What is Food Tracker MCP?
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.
How to use Food Tracker MCP?
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.
Key features of Food Tracker MCP
- Search food products by barcode or keyword
- Analyze nutritional content of food products
- Create meal plans based on nutrition goals and dietary restrictions
- Track food consumption with meal logging
- Manage dietary restrictions and allergies
- Check product compatibility with user restrictions
- View food logs and nutrition summaries
Use cases of Food Tracker MCP
- Set up a new user with dietary restrictions (e.g., gluten allergy, vegetarian)
- Scan a product barcode and log consumption for a meal
- Check if a product is compatible with a user’s restrictions
- Analyze nutrition details of a specific food product
- Retrieve a user’s food log for a given date
FAQ from Food Tracker MCP
What runtime and dependencies are required?
Python 3.8 or higher, plus the packages httpx, fastmcp, and pydantic. A virtual environment is recommended.
Where does Food Tracker MCP store data?
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.
How do I start the server?
Run python food_tracker.py in the project directory after installing dependencies. The server will be ready to receive commands.
Does the server require internet access?
Yes, because it connects to the OpenFoodFacts API to fetch product information.
Can I extend the MCP?
Yes, the README suggests adding new nutritional analysis features, diet plans, recipe suggestions, reports, or social features.
Frequently asked questions
What runtime and dependencies are required?
Python 3.8 or higher, plus the packages `httpx`, `fastmcp`, and `pydantic`. A virtual environment is recommended.
Where does Food Tracker MCP store data?
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`.
How do I start the server?
Run `python food_tracker.py` in the project directory after installing dependencies. The server will be ready to receive commands.
Does the server require internet access?
Yes, because it connects to the OpenFoodFacts API to fetch product information.
Can I extend the MCP?
Yes, the README suggests adding new nutritional analysis features, diet plans, recipe suggestions, reports, or social features.
Basic information
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