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    An MCP server that converts structured cycling workout specs into MyWhoosh .zwo and Garmin Connect workout files, with tools for validation, description, and rendering. It also includes skills for uploading workouts to both platforms.
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    MIT
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    MCP server that lets you ask questions about your Garmin training history in plain language. It ingests FIT files into DuckDB locally and exposes typed tools for analyzing activities, streams, and summaries.
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    MIT
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    Local-first MCP server that reads Apple Health export files (export.xml/zip) and exposes activity, sleep, HRV, and workout data to AI agents, keeping all data on your machine.
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    A Model Context Protocol server that connects Claude to Hevy workout logs, enabling workout reading, routine creation, and training analysis.
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    Enables AI agents to interact with a personal YAZIO nutrition diary, including searching products, reading and writing diary entries, and analyzing nutrition trends.
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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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    Enables access to WHOOP fitness and health data through all WHOOP v2 API endpoints. Supports OAuth 2.0 authentication and provides comprehensive access to user profiles, physiological cycles, recovery metrics, sleep analysis, and workout data.
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    MCP server for the Hevy workout tracker API that allows reading and writing workouts, routines, exercise templates, and body measurements.
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    Enables reading and syncing Xiaomi Mi Fitness health data (steps, heart rate, sleep, workouts) from the Chinese cloud region to a local SQLite database via MCP tools.
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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.
    MIT
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    MCP server that mirrors your Garmin data into a personal database and exposes tools for health summaries, training load, muscle readiness, and race analysis, with optional chat-driven insights via stdio or HTTP.
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    MCP server for Hevy that fetches live workout data and computes analytics like e1RM, PRs, volume, and consistency, while enabling writes for routines, folders, and body measurements without modifying workout history.
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    MIT