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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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    MIT
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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.
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    136 PyPI
    MIT
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    Enables AI assistants to interact with Intervals.icu fitness tracking and wellness data, allowing users to fetch, filter, and group activities or health metrics. It provides structured summaries of workouts and physical well-being through natural language queries.
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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.
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    MIT
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    Provides a unified MCP interface to a personal health database, enabling AI agents to sync lifting workouts from Hevy, log food intake against a catalog, and run read-only SQL queries to cross-reference training and nutrition data.
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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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    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.
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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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    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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    An MCP server that interfaces with the Hevy fitness tracking API, enabling AI assistants to manage workouts, routines, exercise templates, and more via natural language.
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    53,090 npm
    MIT
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    Enables AI assistants like Claude to interact with TrainingPeaks, allowing users to query workouts, build structured intervals, track fitness trends, and add comments through natural language, with automatic secure login.
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    MIT