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"Connecting OpenAI Codex with antigravity concepts or technology" matching MCP servers:

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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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    Enables AI assistants to search the doktor.mx directory for over 56,000 verified doctors and medical specialists across Mexico. It provides tools for verifying professional licenses, finding specialists by symptoms or conditions, and checking medical insurance compatibility.
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    MIT
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    An MCP server that provides access to Tekuila restaurant menus with AI-powered health recommendations and meal planning. It enables users to retrieve daily or weekly menus and receive intelligent nutritional analysis through clients like Claude Desktop and Cursor.
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    MIT
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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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    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.
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    MIT
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    Enables AI-driven weekly meal planning with structured recipes, cooking steps, and grocery lists.
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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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    MIT
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    Enables access to Lose It calorie tracking data including daily summaries with budgets and remaining calories, weekly history, and food logs. Integrates with the Lose It web app API to retrieve nutrition information and dietary entries for monitoring caloric intake.
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    MIT
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    An MCP server specialized in managing and querying gym exercises through a centralized database. It enables users to search for workouts by name or muscle group and retrieve detailed information including sets, repetitions, and rest intervals.
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    Provides raw Garmin Connect data access for training analysis, enabling retrieval of activity summaries, lap data, time-series streams, comments with lactate, wellness metrics, and personal records through an MCP interface.
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    MIT