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"Iterating on UI designs and improving prompts" matching MCP servers:

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    Enables AI assistants to read and analyze Google Fit exported data (activities, daily metrics, workouts, sleep) from Google Takeout, providing tools for queries, resources, and coaching prompts.
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    MCP server that connects Claude or any MCP-capable LLM to your Garmin golf data, enabling natural-language queries on rounds, shots, strokes gained, club distances, course intel, and health-performance correlations from a private local DuckDB cache.
    13
    MIT
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    An MCP server that provides access to detailed exercise-to-muscle mapping data for over 320 exercises and 65 muscles. It enables users to analyze workout coverage, find exercise alternatives based on muscle overlap, and search for specific exercise activation data.
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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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    MIT
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    An MCP server for authoring and managing structured workouts (SuuntoPlus™ Guides) on Suunto watches, with swappable transports (file, Cloud API, or private mobile API) and a coach-oriented domain model that lowers to the display-oriented guide format.
    3
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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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    MIT
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    Integrates with Garmin Connect to retrieve activity data, health metrics, and provide AI-powered training insights and personalized coaching recommendations based on your fitness activities and performance trends.
    14
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    Local-first MCP server that connects AI agents to your Garmin sleep, HRV, Body Battery, stress, training readiness and activities, keeping tokens on your machine.
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    MIT
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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 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.
    127
    MIT