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    Aggregates and analyzes fitness data from multiple sources like Whoop and Strava through a modular adapter architecture. It enables users to monitor health metrics, track activities, and gain insights into sleep, recovery, and training performance.
    1
    MIT
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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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    Provides comprehensive running performance calculations including VDOT, training paces, race time predictions, velocity markers, and heart rate zones using Jack Daniels, Greg McMillan, and Riegel methodologies.
    9
    MIT
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    Local MCP server that connects Claude Desktop with Garmin and Apple Health data to read training and recovery, estimate heart rate and pace zones, analyze performance, and create structured workouts.
    22
    MIT
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    An MCP server that enables interaction with the Strava API v3 to manage fitness activities, athlete profiles, segments, and routes. It supports retrieving detailed performance metrics, exploring geographic data, and managing club information through natural language.
    45
    ISC
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    Enables AI assistants to access and analyze intervals.icu training data including activities, fitness metrics (CTL/ATL/TSB), wellness stats, and calendar events. Supports natural language querying of athletic performance for training insights and workout planning.
    6
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    An MCP server that provides access to Garmin Connect fitness, health, and training data through 61 specialized tools. It enables users to query activities, sleep metrics, and performance stats directly within AI clients like Claude or Cursor.
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    174
    MIT
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    A Model Context Protocol (MCP) server for Intervals.icu integration. Access your training data, wellness metrics, and performance analysis through Claude and other LLMs.
    48
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    MIT
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    Integrates with the Strava API to allow AI assistants to access fitness data including athlete profiles, activity history, and segment statistics. It enables users to query detailed performance metrics and explore geographic segment data through natural language commands.
    8
    45
    MIT
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    Connects Claude to the Strava API to provide direct access to fitness data, including athlete statistics, detailed activity logs, and time-series performance metrics. It enables users to analyze training progress, compare workouts, and retrieve specific segment details through natural language queries.
    8
    45
    ISC
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    A private, read-only MCP server that gives local Codex and Claude Desktop sessions access to athletics and wellness data from a Garmin Forerunner 55. It runs locally over stdio, exposes read-only tools for daily health, recovery, performance, and workouts, and caches data in SQLite.
    8
    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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    A Model Context Protocol server that integrates Garmin Connect data with LLMs to provide personalized running analysis and training plans. It enables users to monitor performance metrics, manage training loads, and receive data-driven workout suggestions based on health indicators like VO2 Max and recovery status.
    43
    5
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    Provides comprehensive access to Strava API for marathon training and race analysis, enabling language models to query athlete data, analyze training patterns, track performance metrics, monitor heart rate zones, and detect injury risks.
    1
    MIT
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    Enables Claude to access your MyFitnessPal diary—foods, portions, meal and daily nutrition totals, water, exercise, steps, and weight—through a custom connector on web, desktop, and mobile.
    19
    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