What is the Food Tracker MCP?

The Food Tracker MCP is a Model Context Protocol (MCP) server that connects Claude AI with the OpenFoodFacts database to create an intelligent nutritional assistant. It allows users to track food consumption, analyze nutrition, and manage dietary restrictions.

How does the Food Tracker MCP work?

The MCP integrates with the OpenFoodFacts database to provide information about food products. Users can interact with the MCP through Claude AI to search for products, analyze nutritional content, log food consumption, and manage dietary restrictions.

What are the key features of the Food Tracker MCP?

Key features include searching for food products, analyzing nutritional content, creating meal plans, tracking food consumption, managing dietary restrictions, and viewing food logs and nutrition summaries.

How do I install the Food Tracker MCP?

Installation involves cloning the repository (if available) or downloading the food_tracker.py file, creating a virtual environment, activating it, and installing the required dependencies using pip.

How do I run the Food Tracker MCP server?

Run the server using the command python food_tracker.py in your terminal after navigating to the directory containing the food_tracker.py file.

How do I use the Food Tracker MCP with Claude AI?

Register the MCP with Claude by following Anthropic’s documentation, providing the necessary information and endpoint. Once registered, you can interact with the Food Tracker through Claude by invoking the MCP’s tools.

What are the available tools that Claude can access through the MCP?

The available tools include get_product_by_barcode, search_products, manage_user_restrictions, check_product_compatibility, analyze_nutrition, log_food_consumption, and get_user_food_log.

How do I add a dietary restriction using the MCP?

Use the manage_user_restrictions tool with parameters like user_id, action (set to “add”), restriction_type, restriction_value, severity, and notes to add a dietary restriction.

How do I log food consumption using the MCP?

Use the log_food_consumption tool, providing parameters like user_id, barcode, quantity, and meal_type to log food consumption for a user.

Where is the data stored by the Food Tracker MCP?

The Food Tracker MCP stores data locally in JSON files. User profiles are stored in ./data/users/{user_id}.json, and food logs are stored in ./data/logs/{user_id}_{date}.json.

How can I extend the functionality of the Food Tracker MCP?

You can extend the MCP by adding new nutritional analysis features, implementing more detailed diet plans and goals, adding recipe suggestions, creating reports and visualizations of nutrition data, and implementing social features.

What should I do if I encounter connection issues?

Ensure you have internet access, as the MCP connects to the OpenFoodFacts API. If issues persist, check your network settings and ensure no firewalls are blocking the connection.

What if product information is incomplete?

Incomplete product information may be due to limitations in the OpenFoodFacts database. You can contribute to the database by adding or updating product information.

What does UBOS platform have to do with it?

UBOS is a full-stack AI Agent Development Platform. UBOS focused on bringing AI Agent to every business department. UBOS platform help you orchestrate AI Agents, connect them with your enterprise data, build custom AI Agents with your LLM model and Multi-Agent Systems.