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mcp-opennutrition

mcp-opennutrition is a Model Context Protocol (MCP)-based server for accessing the OpenNutrition food database. The database contains over 300,000 food entries, nutrition data, and barcode lookup functionality. OpenNutrition integrates authoritative public sources such as USDA, CNF, FRIDA, and AUSNUT, aiming to solve the problem of fragmented and unreliable nutrition data and provide developers and researchers with transparent, comprehensive, and freely accessible nutrition data. This MCP server supports searching for foods by name, paginated browsing of food lists, retrieving detailed nutrition information by food ID, and finding foods using EAN-13 barcodes. The server can run entirely locally, with all data processing and queries performed locally, requiring no external API calls, ensuring privacy and fast responses.

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About this tool

Purpose

mcp-opennutrition is a Model Context Protocol (MCP) server that provides MCP-enabled AI assistants such as Claude and Cline with access to the OpenNutrition food database. The OpenNutrition database contains over 300,000 food entries, nutrition data, and barcode lookup functionality, and integrates authoritative public sources such as USDA, CNF, FRIDA, and AUSNUT, aiming to solve the problem of fragmented and unreliable nutrition data and provide developers and researchers with transparent, comprehensive, and freely accessible nutrition data.

Main capabilities

  • Search by name: Find foods by food name, brand, or partial match.
  • Browse foods: Get a paginated list of all available foods.
  • Get by ID: Retrieve detailed nutrition information using a food ID.
  • Barcode lookup: Find foods using an EAN-13 barcode.

The server uses the OpenNutrition dataset to provide comprehensive nutrition profiles including macronutrients, vitamins, and minerals.

Usage

Docker (recommended)

The simplest way to run the server is via Docker, with no build step required. After running the container, add it to the MCP configuration.

Local build

  1. Install dependencies:npm install
  2. Build the project:npm run build
  3. Add to the MCP configuration (the same Node version as when building the project must be set):
"mcp-opennutrition": {
  "command": "/Users/YOUR.USERNAME/.nvm/versions/node/v20.19.0/bin/node",
  "args": ["/ABSOLUTE/PATH/TO/PARENT/FOLDER/mcp-opennutrition/build/index.js"]
}

After configuration is complete, the MCP server runs entirely on the local machine, automatically providing Claude/Cline with food and nutrition query capabilities. All data processing and queries are performed locally, with no external API calls, ensuring privacy and fast responses.

Applicable scenarios

Suitable for scenarios that require integrating food nutrition data query capabilities into AI assistants, such as querying ingredient nutrition information based on a recipe (e.g., a brownie recipe), identifying foods by barcode, or searching for foods by name or brand. Suitable for developers, researchers, and users concerned about dietary nutrition.

Limitations

The materials do not provide further details about fees, pricing, platform support scope, performance metrics, or specific usage steps.

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