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    An AI recipe recommendation server based on the MCP protocol, providing functions such as recipe query, classification filtering, intelligent dietary planning, and daily menu recommendation.
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    Apache 2.0
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    Solar vitamin D: whether the sun where you are can make vitamin D right now, how many minutes your Fitzpatrick skin type needs for a target dose, which months of the year synthesis is possible at your latitude, and how much a sun session produced. Computed from solar geometry, a clear-sky UV model with ozone and altitude, and live Open-Meteo UV data.
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    MIT
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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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    MIT
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    Provides a unified MCP interface to a personal health database, enabling AI agents to sync lifting workouts from Hevy, log food intake against a catalog, and run read-only SQL queries to cross-reference training and nutrition data.
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    A TypeScript server that acts as a bridge to the Strava API, enabling LLMs to access users' activities, routes, segments, and athlete data through natural language interaction.
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    MIT
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    Enables AI assistants to recommend recipes, plan weekly meals, and solve the "what to eat today" problem by providing access to a comprehensive Chinese recipe database with smart filtering by categories, allergies, and dietary restrictions.
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    ISC
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    Provides AI agents with access to Hevy workout data, allowing them to manage workouts, routines, exercises, and body measurements through a Dockerized SSE endpoint.
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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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    Exposes Whoop fitness data (recovery, sleep, strain, workouts) to Claude for use as a daily training coach, enabling natural language queries about your health metrics and training readiness.
    MIT
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    MCP server that lets a hosted LLM securely read a local family health archive and deposit structured reports into an inbox, with a read-biased tool surface and strict path/token enforcement.
    MIT
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    MCP server for workout-file conversion: convert, validate, and inspect FIT, TCX, ZWO, and Garmin Connect files, with round-trip-safe conversions through the KRD canonical JSON format. Runs locally over stdio via npx -y @kaiord/mcp. Part of the open-source, local-first Kaiord training platform.
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    MIT