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Fitness Tracking

Integration with fitness tracking apps and devices. Enables access to workout data, activity history, performance metrics, and training analytics.

MCP ServersBrowse all →

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    Enables users to describe workouts in plain English and have them created as structured Garmin Connect workouts with pace, HR, power, cadence targets, and repeat blocks. Also provides full workout lifecycle management including listing, updating, deleting, and scheduling to the calendar.
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    MIT
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    MCP server for local fitness-data extraction and analysis from Garmin Connect, Intervals.icu, and Strava. Provides read-only analytical tools over DuckDB and targeted Strava enrichment.
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    AGPL 3.0
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    MCP server for the Google Health API: heart rate, activity, sleep, SpO2, HRV, ECG and irregular-rhythm notifications, read into a local SQLite cache for fast offline queries and trend analysis. OAuth 2.0 with automatic token refresh, incremental sync, a cache-only offline mode, and a doctor command that diagnoses a setup without spending quota.
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    GPL 3.0
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    Provides six deterministic, source-attributed hydration calculators (water intake, dehydration check, pregnancy intake, kidney-safe intake, athlete plan, energy optimization) as MCP tools, enabling AI clients to call them via stdio without custom HTTP coding.
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    MIT
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    Enables Claude Desktop to access and analyze Garmin wearable health data including sleep, HRV, Body Battery, and activity metrics. Users can query their health trends, track recovery, and generate interactive HTML dashboards using natural language.
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    MIT
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    Enables users to interact with their Strava data through natural language to analyze workouts, track fitness progress, and explore routes. It supports retrieving detailed activity stats, heart rate data, and segment insights directly within AI assistants.
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    MCP server that reads Zepp/Amazfit health and workout data, exposing tools for daily summaries, sleep, heart rate, and workout details to any MCP client.
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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.
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    MCP server that provides local caching, sync, and tools for Zepp Life health data including steps, sleep, heart rate, workouts, and body measurements, supporting both file exports and cloud session access.
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    Gives Claude access to your WHOOP health data including recovery, sleep, workouts, cycles, body measurements, and profile via the WHOOP Developer API.
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    An AI-powered running coach that connects Claude to your Strava data, providing personalized training plans, progress tracking, and coaching feedback through a web dashboard.
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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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    An MCP server that gives LLMs access to Garmin Connect data, including training, recovery, sleep, stress, VO2 Max, and running summaries for personalized fitness advice.
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    A local-first, read-only MCP server that provides compact recovery, sleep, strain, HRV, heart-rate, workout, and body-measurement data from WHOOP without sending credentials to a third party.
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    Provides access to Oura Ring health data including sleep, readiness, and resilience metrics through the Oura API, enabling language models to query and analyze personal health information.
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    Exposes personal Garmin Connect data to MCP-capable clients like Claude and Gemini. Enables querying daily stats, heart rate, sleep, activities, and managing workouts.
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    An MCP server and CLI for logging food to Lose It!, enabling food search, diary management, meal logging, and weight recording via unofficial API.
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    BSD Zero Clause
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    Local-first MCP server that reads Apple Health export files (export.xml/zip) and exposes activity, sleep, HRV, and workout data to AI agents, keeping all data on your machine.
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    MIT

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