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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.
    6
    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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    Ask your Oura Ring about sleep, readiness, activity, stress and heart rate in ChatGPT or Claude, in any language. Read-only, 10 task-oriented tools; runs in a sandbox demo mode with no credentials.
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    17 npm
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    Provides Claude with real-time access to local health data including sleep, recovery, strain, and workouts from WHOOP and Apple Health, enabling informed context-aware interactions.
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    Exposes the Oura API v2 as an MCP server with tools to query all 19 data collections (e.g., sleep, heartrate) with automatic pagination and explicit truncation warnings.
    4
    136 PyPI
    MIT
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    MCP server to read daily activity, sleep, heart rate, and body metrics from Google Health API, allowing AI assistants like Claude to access your health data. Optionally syncs health metrics to an Obsidian vault.
    5
    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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    25 npm
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    MIT
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    Provides AI assistants with read-only access to an athlete's Intervals.icu training data, including activities, wellness metrics, zones, and planned events, for use with MCP clients like ChatGPT and Claude.
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    MIT
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    Connects Claude to your Strava fitness data, enabling natural language queries about your training history such as activities, stats, and routes.
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    Hosted MCP server that syncs health data from Apple Health, Fitbit, Oura, and Google Health Connect, enabling Claude and ChatGPT to query workouts, sleep, nutrition, and recovery in plain English with interactive charts.
    2
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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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    25 npm
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    Exposes real-time health data from the Ultrahuman Ring to AI agents via the Model Context Protocol, providing optimized summaries with trend analysis and actionable insights.
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