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    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.
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    A TypeScript server that acts as a bridge to the Strava API, enabling LLMs to access users' activities, routes, segments, and athlete data through natural language interaction.
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    Trainzilla MCP connects Claude to your Trainzilla coach account, turning your client roster, programming, and habit tracking into something you can manage conversationally. Built for fitness coaches running their practice on Trainzilla, it lets Claude pull up client profiles and metrics, build and review workout and diet plans, create and assign habits, run quick calculations (TDEE, macros, 1RM),
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    A Model Context Protocol server that provides language models with access to Strava API data, allowing them to query and analyze athlete activities from Strava.
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    A Python-based Model Context Protocol server that provides AI assistants with access to Oura Ring health and fitness data across 15+ endpoints. It enables querying metrics like sleep, activity, readiness, and cardiovascular health through simple authentication and date-range filtering.
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    MIT
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    A production-ready MCP server for the Hevy fitness API that exposes 27 tools for reading, writing, and analyzing workout data, enabling LLM-driven personal trainer workflows.
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    MIT
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    A read-only MCP server for the Apex Rides API, deployed as a Cloudflare Worker, providing tools to browse popular classes, search workouts, get class details, and list instructors.
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    MIT
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    An MCP server specialized in managing and querying gym exercises through a centralized database. It enables users to search for workouts by name or muscle group and retrieve detailed information including sets, repetitions, and rest intervals.
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    A Model Context Protocol (MCP) server that connects AI assistants to your MyFitnessPal data, enabling reading food diaries, nutrition goals, weight measurements, and more via MFP's web scraping.
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    MIT
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    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.
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    MIT