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    Enables MCP clients to connect to a privacy-first, self-hostable workout planning and training log, allowing coaching agents to preview and apply program changes while accessing training data through OAuth-protected endpoints.
    AGPL 3.0
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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
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    Enables AI agents like Claude Desktop, Cursor, and VS Code to connect directly to COLMI R02/R03 and compatible smart rings over local Bluetooth LE, exposing tools for ring scanning, battery and firmware status, activity and sleep/recovery insights, real-time heart rate and SpO2 vitals, 3-axis motion sampling, clock sync, and physical LED blinking. Runs fully locally with no vendor cloud, accounts, or subscriptions.
    8
    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.
    9
    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.
    10
    10
    1
    MIT
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    A local MCP server that caches Garmin Connect data in SQLite for fast, read-only queries, with tools for bulk import, rate-limited sync, and failure alerts.
    9
    MIT
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    Enables AI assistants to access and modify a user's real GymTimer workout and nutrition data stored in private iCloud, allowing natural-language queries about training history and the creation of workout templates and meal plans.
    21
    MIT
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    Enables AI agents to interact with a personal YAZIO nutrition diary, including searching products, reading and writing diary entries, and analyzing nutrition trends.
    17
    125
    MIT
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    Enables reading and writing MyFitnessPal data—including food diary entries, custom foods, saved meals, recipes, exercise, measurements, water, and nutrition goals—through 33 MCP tools using your existing browser session for authentication.
    33
    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
    12
    MIT
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    MCP server for the Hevy workout tracker API that allows reading and writing workouts, routines, exercise templates, and body measurements.
    22
    17
    MIT