This is an MCP (Model Context Protocol) server for integrating with the Nutritionix API, enabling AI agents to access food search, nutrition data, and exercise calorie estimates via natural language input.

The goal of this project is to expose Nutritionix's functionality through MCP-compatible tools that can be used seamlessly by large language models and agent frameworks.

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🧠 What is MCP?

MCP (Model Context Protocol) is a lightweight protocol designed to let AI agents interact with external tools and APIs in a structured and modular way. Think of it like USB for AI — this server acts as a "driver" for the Nutritionix platform.

With this MCP server, AI models can:

• 🔍 Search for common and branded food items
• 🍽️ Parse natural language meals into nutritional breakdowns
• 🏃 Estimate calories burned from exercises like running, cycling, or yoga

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🚀 How to Run

To use this MCP server, you'll need:

✅ Prerequisites

• Python 3.11+
• uv – a modern Python package manager
• A supported LLM (e.g., Claude)
• A Nutritionix API App ID and App Key – get them at developer.nutritionix.com

Add this to Claude Desktop config

{
  "mcpServers": {
    "nutritionix-mcp": {
      "command": "uvx",
      "args": [
        "nutritionix-mcp-server",
        "--app-id",
        "YOUR APP ID",
        "--app-key",
        "YOUR APP KEY"
      ]
    }
  }
}

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🤝 Contributions Welcome!

Whether you're into nutrition tech, AI agent development, or API tooling — we’d love your help improving this project. You can contribute by:

• Adding new tools (e.g., barcode search, food logging)
• Improving response formatting
• Writing tests or documentation
• Suggesting new ideas via Issues or Discussions

Feel free to fork, explore, and submit a PR. Let’s make agent-integrated nutrition smarter, together. 🧠🥗

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