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    A universal fitness intelligence layer for AI assistants like Claude, ChatGPT, and Copilot, enabling user profiles, workout/diet plans, calendar scheduling, and gamification via MCP and REST APIs.
    7,813
    MIT
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    Your AI running coach that actually remembers. An MCP server with persistent memory that connects your Strava data to Claude — tracking your zones, pace trends, injuries, and goals across sessions so coaching advice stays current.
    MIT
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    A health-data MCP server with per-user authorization using JWT tokens, enabling secure access to fitness data like profiles, progress, meal logs, workout logs, and weight logs through MCP tools.
    MIT
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    Minimalist Strava integration for Claude with 7 focused tools for querying athlete stats, activities, zones, and segment analysis.
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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.
    27
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    MIT
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    A local, read-only Model Context Protocol server for an athlete's Strava profile and activities, enabling retrieval of profile data, activity lists (with paging and date filters), and detailed activity information via standard input/output for MCP hosts.
    3
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    MIT
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    MCP server integrating Foodvisor nutrition API for food search, meal logging, daily summaries, and progress tracking via LLM agents like Claude.
    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.
    1
    MIT
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    Brings Garmin training data into Claude via Intervals.icu, enabling querying of activities, wellness, and planned workouts, as well as creating structured workouts that sync back to the Garmin watch.
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    MIT
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    Exposes Whoop fitness data (recovery, sleep, strain, workouts) to Claude for use as a daily training coach, enabling natural language queries about your health metrics and training readiness.
    MIT