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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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    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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    Minimalist Strava integration for Claude with 7 focused tools for querying athlete stats, activities, zones, and segment analysis.
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    An MCP server that provides access to detailed exercise-to-muscle mapping data for over 320 exercises and 65 muscles. It enables users to analyze workout coverage, find exercise alternatives based on muscle overlap, and search for specific exercise activation data.
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    Local-first MCP server that connects AI agents to your Garmin sleep, HRV, Body Battery, stress, training readiness and activities, keeping tokens on your machine.
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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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    Enables users to interact with the Griptonite indoor climbing app, allowing them to log climbs, browse routes and grades, and retrieve activity feeds and rankings.
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    MIT
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    Apple HealthKit → PostgreSQL sync + MCP server for Claude Code, Cursor, and Ollama. Open-source iOS app with reliable background sync (HKObserverQuery). 11 tools covering health summary, sleep, HRV trends, workouts, daily snapshots, metric stats, period comparison, and coaching briefs. Supports Supabase, Neon, and self-hosted Postgres. Privacy-first: your data goes to your own database.
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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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    Analyze iGPSport cycling data with natural language, computing derived training metrics (NP, IF, TSS, CTL, ATL, TSB) locally via MCP.
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    MIT