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    Enables AI assistants to answer food safety and shelf-life questions using USDA-grade data, with tools for shelf life, safety checks, storage tips, and waste cost calculations.
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    MIT
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    Condition-aware ingredient & product safety intelligence for AI agents. Every answer carries a claim-level evidence attestation, verdict, an evidence tier, and a citation – curated against authoritative sources (LactMed, InfantRisk, PubMed, DSLD, DermNet, EU CosIng) by Health AI. Hosted MCP server – no install, no key. Endpoint: https://mcp.healthai.com (Streamable HTTP, JSON-RPC 2
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    MIT
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    Provides comprehensive running performance calculations including VDOT, training paces, race time predictions, velocity markers, and heart rate zones using Jack Daniels, Greg McMillan, and Riegel methodologies.
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    MIT
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    Enables AI assistants to manage recipes, meal plans, and shopping lists in Mealie through natural language, supporting CRUD operations and URL-based recipe imports.
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    MIT
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    A generic MCP server for tracking any entity type (e.g., weight, workouts, books) without predefined schemas, using SQLite with JSON columns for flexible data storage and querying.
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    MIT
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    Enables Claude Desktop to access and analyze Garmin wearable health data including sleep, HRV, Body Battery, and activity metrics. Users can query their health trends, track recovery, and generate interactive HTML dashboards using natural language.
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    MIT
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    Exposes WHOOP recovery, sleep, strain, and workout metrics to MCP-compatible AI assistants using OAuth 2.0 authentication, enabling daily wellbeing snapshots, trend analysis, and workload recommendations.
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    Enables AI assistants to search for recipes, get nutritional information, find ingredients, and more through the Spoonacular Food API using natural language.
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    Local MCP server for the WHOOP API v2 that provides tools to access recovery, sleep, strain, and workout data, with local history and JSON export.
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    Enables AI agents to generate budget-disciplined, allergy-safe weekly meal plans, shopping lists, and meal swaps using a fully local deterministic engine.
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    A Model Context Protocol (MCP) implementation for Fitbit, enabling AI assistants to access and analyze your Fitbit health and fitness data. Disclaimer: This is an unofficial integration built using Fitbit's public API and is not affiliated with or endorsed by Fitbit Inc.
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    MIT