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.
Enables creating workout plans, tracking progress, suggesting exercises, and calculating training volume through natural language, compliant with MCP protocol.
Connects WHOOP fitness data to Poke AI assistant, enabling natural language queries for recovery scores, sleep analysis, strain tracking, and healthspan metrics.
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.
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 read-only access to Oura ring biometrics via the Oura API, enabling Claude to query daily summaries, sleep, readiness, stress, workouts, baselines, and heart rate data. Designed to complement a Strava connector for joint analysis of training and recovery.
Connects WHOOP fitness tracker data to AI assistants like Claude and ChatGPT, enabling natural language queries about recovery, sleep, strain, and trends.
MCP server that enables AI assistants to access Whoop health data including recovery, sleep, workouts, and daily strain for personalized health recommendations.
A local-first, read-only MCP server that provides compact recovery, sleep, strain, HRV, heart-rate, workout, and body-measurement data from WHOOP without sending credentials to a third party.
A Model Context Protocol server for TrainingPeaks with an analytics focus — enabling real-time querying of training data, performance trends, CTL/ATL/TSB analysis, and training load optimization through Claude Desktop.
Connects AI agents to Iridium fitness data to query workout history, nutrition logs, and body measurements. It enables users to track exercise progress, training volume, and personalized trainer analysis through natural language.
Connects Sensor Bio wearable data to AI assistants via the Model Context Protocol, enabling queries about sleep, heart rate, activity, and other biometrics.