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    An MCP server that provides a USDA-accurate food database with deterministic macro math, enabling tools like list_foods, get_food, calculate_macros, filter_by_diet, build_meal, and list_available_tags. It allows Claude to look up nutrition facts and solve for exact macro targets offline, without AI or network.
    6
    MIT
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    Claude Code plugin and MCP server that nudges you to take outdoor breaks based on local weather, sunset timing, and session streaks. Exposes check_grass_conditions, suggest_activity, log_touch_grass, and get_stats tools — fully local, no API keys, no cloud storage.
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    2 npm
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    MIT
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    Unofficial, self-hosted MCP server that connects Claude or ChatGPT to your own FatSecret food diary. It drafts entries from a description, a plate photo or a nutrition label, saves them only after you confirm, and changes or removes entries the same way. It also reads a day or several weeks against your calorie and macro targets.
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    147 PyPI
    5
    MIT
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    Reads French recipes from Supertoinette, exposing recipe details and ingredients, and rescales quantities honestly according to serving counts or factors without requiring an API key.
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    475 npm
    MIT
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    MCP server that lets you ask questions about your Garmin training history in plain language. It ingests FIT files into DuckDB locally and exposes typed tools for analyzing activities, streams, and summaries.
    9
    MIT
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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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    20 npm
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    MIT
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    Enables users to answer California drinking water questions about public water systems, SAFER risk/violation status, source-water chemistry, school lead sampling, and latest tap/treated-water results by ZIP code or water system ID, using curated Databricks Gold views over State Water Board open data.
    7
    MIT
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    Query Apple Health export data with an LLM via a semantic layer that avoids common data traps, enabling accurate natural-language queries about health metrics. Optionally imports CPAP therapy data for correlation.
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    MIT
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    Enables browsing the Ptitchef recipe category tree and reading its recipes without an API key or account.
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    653 npm
    MIT
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    Enables assistants and agents to look up sourced nutrition, glycemic load, and micronutrient data for Indian dishes and ingredients by amount in grams or household measures, including meal totals, nutrient rankings, and estimated daily targets.
    5
    MIT
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    Runs entirely locally to provide calm, animated breathing sessions that open in a browser or as an artifact, with tools for matched or custom sessions, pattern listings, and a breathing-break prompt, while collecting no data.
    3
    143 npm
    MIT
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    Provides access to Danish food and nutrition data from Open Food Facts and DTU Frida, enabling keyword search, barcode lookup, and detailed food information with per-100g macros and source attribution.
    5
    Apache 2.0
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    Enables AI assistants to generate chronologically organized Korean pregnancy and parenting schedules—vaccinations, health checkups, leave, and application deadlines—from a due date or child's birthday, with optional API-key features such as night clinic and recall lookups.
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    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.
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    MIT
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    Unofficial MCP server for Fitatu, the Polish calorie counter: read and log food, weight, water, body measurements and workouts, check calories and macros left, set goals and get weekly reports. 47 tools (26 read-only), read-only and demo modes, stdio or HTTP with a token, free and Premium accounts.
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    138 PyPI
    21
    MIT
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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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    42 npm
    4
    MIT