Enables creating workout plans, tracking progress, suggesting exercises, and calculating training volume through natural language, compliant with MCP protocol.
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.
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.
Connects WHOOP fitness data to Poke AI assistant, enabling natural language queries for recovery scores, sleep analysis, strain tracking, and healthspan metrics.
MCP server for tracking nutrition meals and workouts, integrating with claude.ai to manage food logs, macros, exercise catalogs, and generate daily/weekly summaries.
Exposes over 90 Garmin Connect tools for tracking activities, health metrics, and training data through the Model Context Protocol. It is optimized for Poke compatibility and supports deployment to Render via HTTP.
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.
Enables Claude to act as a personal health coach by connecting to Garmin wearable data and Notion workspace for automated calorie tracking, photo food logging, and coaching insights.
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.
Enables creating, previewing, scheduling, and managing Garmin Connect workouts, plus reading activities and health metrics, all through a local MCP server.
MCP server for the Hevy fitness tracking app, enabling management of workouts, routines, exercise templates, folders, and webhooks through AI assistants.
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.