Hevy MCP
A TypeScript MCP Server for interacting with Hevy Workout App in LLMs
Overview
what is Hevy MCP?
Hevy MCP is a TypeScript Model Context Protocol (MCP) server designed to interact with the Hevy workout tracking API, allowing AI assistants to access and analyze workout data.
how to use Hevy MCP?
To use Hevy MCP, clone the repository, install dependencies, configure your Hevy API key, and restart your LLM environment. You can then query your workout data through your AI assistant.
key features of Hevy MCP?
- Retrieves workout history from the Hevy API.
- Implements the Model Context Protocol for seamless AI integration.
- Simple setup with configurable options.
use cases of Hevy MCP?
- Analyzing workout history to track fitness progress.
- Generating personalized workout recommendations based on past performance.
- Integrating with AI tools for enhanced fitness insights.
FAQ from Hevy MCP?
- What do I need to run Hevy MCP?
You need Node.js (v18 or higher), a Hevy API key, and an LLM that supports the Model Context Protocol.
- Can I customize the queries?
Yes! You can ask your AI assistant to summarize workouts or recommend new workouts based on your history.
- Is there support for additional features?
Currently, the server provides basic workout retrieval, but suggestions for additional methods are welcome.
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