HevyMCP - AI-Powered Fitness Assistant

by kani3894

266 downloads
Not rated
GitHub

About

Python MCP server for Hevy fitness app. Log workouts with natural language, search exercises, manage routines. Features web interface, demo mode, and 22 MCP tools.

Details

Author
kani3894
Downloads
266
Categories
AI

- Natural language workout logging (e.g., "bench press 3x8 at 135 lbs")
- Smart exercise matching with fuzzy logic
- Routine and folder management
- Web interface with demo mode
- 22 MCP tools for various fitness tasks

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:

  1. Download and install Highlight from highlightai.com/download
  2. Navigate to the plugins tab and select "Add Custom Plugin"
  3. Configure the plugin with the settings below
    Plugin Name HevyMCP - AI-Powered Fitness Assistant
    Command (node, npx, python, etc.)

    Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.

  4. Enable "Start Automatically" if you want the plugin to start when Highlight launches

From the repository

Install and configure the HevyMCP server, then use its 22 MCP tools through any MCP client. A web interface with demo mode is available for testing.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "hevymcp - ai-powered fitness assistant": {
            "hevymcp": {
                "command": "python",
                "args": [
                    "mcp_server.py"
                ],
                "env": {
                    "HEVY_API_KEY": "your_hevy_api_key"
                }
            }
        }
    }
}

McpServers

{
    "hevymcp": {
        "command": "python",
        "args": [
            "mcp_server.py"
        ],
        "env": {
            "HEVY_API_KEY": "your_hevy_api_key"
        }
    }
}

Features

- Natural language workout logging ("bench press 3x8 at 135 lbs") - Smart exercise matching with fuzzy logic - Routine & folder management - Web interface with demo mode - 22 MCP tools for AI assistants
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