Nutritionix MCP Server
About
An MCP server that integrates with the Nutritionix API to provide nutrition data, meal insights, and food logging capabilities. Ideal for AI agents managing health, fitness, or dietary workflows.
Details
- Author
- MCP-Forge
- Downloads
- 354
- Categories
- Other, API
Jump to
- Search common and branded food items
- Parse natural language meals into nutritional breakdowns
- Estimate calories burned from exercises (e.g., running, yoga)
- Built on the Model Context Protocol for AI agent integration
- Lightweight and easy to run with uv
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Nutritionix MCP ServerCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
To use it, you need Python 3.11+, uv, a supported LLM (e.g., Claude), and Nutritionix API credentials. Add the server to your Claude Desktop config with the uvx command, passing your App ID and App Key as arguments. Once configured, the server exposes MCP tools for searching foods, parsing meals, and estimating exercise calories.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"nutritionix mcp server": {
"nutritionix-mcp": {
"command": "uvx",
"args": [
"nutritionix-mcp-server",
"--app-id",
"YOUR APP ID",
"--app-key",
"YOUR APP KEY"
]
}
}
}
}McpServers
{
"nutritionix-mcp": {
"command": "uvx",
"args": [
"nutritionix-mcp-server",
"--app-id",
"YOUR APP ID",
"--app-key",
"YOUR APP KEY"
]
}
}🥦 Nutritionix MCP Server
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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