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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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    1
    MIT
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    Enables AI assistants to read your SisRUN training plan with your own credentials and answer questions about prescribed workouts, like weekly coach plans, in a structured format.
    3
    MIT
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    Local MCP server that connects Claude Desktop with Garmin and Apple Health data to read training and recovery, estimate heart rate and pace zones, analyze performance, and create structured workouts.
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    MIT
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    MCP server that connects Garmin Connect to Claude Desktop, allowing users to query health and fitness data (sleep, workouts, heart rate, HRV, stress, Body Battery, etc.) in plain English and also log weight, hydration, and schedule workouts.
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    MIT
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    Trainzilla MCP connects Claude to your Trainzilla coach account, turning your client roster, programming, and habit tracking into something you can manage conversationally. Built for fitness coaches running their practice on Trainzilla, it lets Claude pull up client profiles and metrics, build and review workout and diet plans, create and assign habits, run quick calculations (TDEE, macros, 1RM),
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    MacroFactor MCP is a local Fueling & Recovery Decision Engine. Give your MCP client a MacroFactor export, optionally add Garmin, and ask for a decision instead of manually comparing nutrition, sleep, body, and training screens.
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    MIT
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    An MCP server for interacting with the Wahoo Cloud API to manage workouts, routes, training plans, and power zones. It enables users to list, retrieve, and create fitness data through secure OAuth 2.0 authentication.
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    GPL 3.0
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    A Model Context Protocol server that provides language models with access to Strava API data, allowing them to query and analyze athlete activities from Strava.
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    MIT
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    Provides local MCP tools to query your own Xiaomi Mi Fitness health data (sleep, workouts, heart rate, etc.) stored in a local SQLite database, enabling AI assistants to access personal health records without exposing credentials.
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    AGPL 3.0
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    Enables Claude to access and analyze Suunto sports watch data, allowing users to ask natural-language questions about their workouts, training metrics, and history.
    MIT
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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 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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    MCP server that turns any MCP-compatible LLM client into a wellness coach grounded in verified public data, offering nutrition, exercise, biometric, and preventive care tools with safety guardrails.
    MIT
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    Unofficial MCP server for Hevy that lets AI assistants design training programs, create routines directly in your Hevy account, and analyze logged workouts.
    6,107
    MIT