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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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    MIT
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    Enables AI assistants to access and analyze Polar device health data, including exercises, heart rate, sleep, and recovery metrics, by preprocessing raw sensor data into compact summaries to avoid context window overload.
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    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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    Enables read-only querying of your own Garmin Connect data — sleep, HRV, resting HR, Body Battery, activities, training volume, body composition, and nutrition — through Garmin's official Personal API using a revocable key. Returns compact, unit-labelled JSON shaped around questions so whole date ranges fit in context.
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    Enables AI assistants like Claude to read a single user's own Strava account through its API: profile and totals, activities with laps, splits, zones and per-second streams, plus segments, routes, gear and clubs. It is strictly read-only, using the user's own Strava API application and OAuth tokens stored locally, and returns model-friendly, context-sized data.
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    MIT
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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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    A lightweight Garmin Model Context Protocol server with 12 curated endpoints for endurance athletes, enabling natural-language queries of activity, training, health, device, and goal data from Garmin Connect.
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    497 PyPI
    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.
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    MIT
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    A Model Context Protocol server that connects Claude to Hevy workout logs, enabling workout reading, routine creation, and training analysis.
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    A Model Context Protocol (MCP) server implementation that interfaces with the Hevy fitness tracking app and its API. This server enables AI assistants to access and manage workout data, routines, exercise templates, and more through the Hevy API (requires PRO subscription).
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    Enables agents to locally analyze Huawei Health export data, retrieve activity summaries, tracks, samples, and health context, and generate structured report evidence with optional environmental data.
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    A Model Context Protocol (MCP) server that fetches sleep, HRV, and training data from the unofficial Coros API and exposes them to AI assistants like Claude, enabling natural language queries about fitness metrics and workout management.
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