Garmin health and fitness data in Claude and ChatGPT via the official Garmin Health API. Hosted remote server with OAuth sign-in — no password sharing.
Enables creating workout plans, tracking progress, suggesting exercises, and calculating training volume through natural language, compliant with MCP protocol.
Read-only MCP server that exposes Apple Health data (steps, workouts, sleep, etc.) from a local SQLite store, allowing AI agents to query health metrics without sending data to hosted services.
Provides LLMs with access to Oura Ring health data including sleep metrics, activity tracking, heart rate, readiness scores, and other wellness insights through the Oura API v2.
AI-powered running course generator that creates custom routes on Seoul's pedestrian network based on natural language requests (distance, elevation, shape), integrating slope, lighting, and facility data.
Enables LLMs to access and analyze biometric and training data via MCP, supporting queries on sleep, performance, nutrition, and training load to generate adaptive training insights.
MCP server for Intervals.icu that enables AI assistants to manage athletic training data, including activities, calendar events, wellness metrics, and workout libraries.
An MCP server that exposes the Hevy fitness API as 22 tools, enabling AI agents to manage workouts, routines, exercise templates, and body measurements through natural language.
An MCP server that interfaces with the Hevy fitness tracking API, enabling AI assistants to manage workouts, routines, exercise templates, and more via natural language.
A Model Context Protocol (MCP) server implementation that interfaces with the Hevy fitness tracking app and its API. This server enables AI assistants to access and manage workout data, routines, exercise templates, and more through the Hevy API (requires PRO subscription).
Enables analysis and retrieval of JEFit workout data through natural language. Provides access to workout dates, detailed exercise information, and batch workout analysis for fitness tracking and progress monitoring.
Enables users to search and retrieve fitness exercise information from the Api Ninjas database. It supports filtering by exercise name, target muscle, type, and difficulty level.
Provides AI agents with access to Hevy workout data, allowing them to manage workouts, routines, exercises, and body measurements through a Dockerized SSE endpoint.