Hevy MCP
by amilz
Hevy MCP is a TypeScript Model Context Protocol server implementation for interacting with the Hevy workout tracking API. It enables AI tools to retrieve and analyze your workout history, helping you gain insights into your fitness journey.
Last updated: N/A
What is Hevy MCP?
Hevy MCP is a server that provides AI assistants with access to your Hevy workout data through the Model Context Protocol. It acts as a bridge between the Hevy API and AI tools, allowing them to retrieve and analyze your workout history.
How to use Hevy MCP?
To use Hevy MCP, you need to clone the repository, install dependencies, build the TypeScript code, and configure your Hevy API key in your LLM. Then, restart your LLM environment and query it about your workout data.
Key features of Hevy MCP
Retrieves workout history from Hevy API
Implements the Model Context Protocol for AI assistant integration
Simple setup with configurable options
Provides a
getWorkoutstool for retrieving user workouts with pagination
Use cases of Hevy MCP
Summarize your last workouts
Recommend a workout based on your workout history
Analyze your workout progress
Gain insights into your fitness journey
FAQ from Hevy MCP
What is the Model Context Protocol?
What is the Model Context Protocol?
The Model Context Protocol (MCP) is a standard for enabling AI models to access and utilize external data sources.
Where do I get my Hevy API key?
Where do I get my Hevy API key?
You can find your Hevy API key in the Hevy Settings under the developer section.
What LLMs are compatible with Hevy MCP?
What LLMs are compatible with Hevy MCP?
Any LLM that supports the Model Context Protocol, such as Claude Desktop, is compatible.
What version of Node.js is required?
What version of Node.js is required?
Node.js version 18 or higher is required.
How do I configure the server?
How do I configure the server?
You need to set up your Hevy API key in your LLM's configuration file, specifying the command and arguments to run the Hevy MCP server.