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    Enables nutrition tracking with Cronometer, including food logging, food search, diary management, and nutrition data retrieval via natural language.
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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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    An MCP server for Garmin Connect that provides access to fitness activities, health statistics, and sleep data by routing requests through a headless browser to bypass API restrictions. It enables users to query detailed metrics like heart rate zones, body battery, and GPS tracks using any MCP-compatible client.
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    AGPL 3.0
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    Enables users to query Apple Health metrics, workouts, and trends from CSV files exported via the Health Auto Export app. It allows MCP clients to analyze health data such as heart rate, sleep stages, and activity levels directly from local iCloud Drive storage.
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    An MCP server that securely syncs and queries your health data from Apple Health, storing it in your own Supabase Postgres database and exposing tools for AI assistants to retrieve weight, calories, macros, and more.
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    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.
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    MIT
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    MCP server for meal planning and grocery list generation, enabling recipe storage, meal plan creation, and automated grocery lists with ignored ingredients.
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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.
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    MIT