"Information about MongoDB, a database system" matching MCP servers:

Provides intelligent access to the USDA nutrition database through AI assistants, enabling users to search foods, compare nutritional content, find foods high in specific nutrients, and query authoritative nutrition data across 7,146+ food items through natural language.

Exposes Garmin Connect health and activity data (steps, sleep, heart rate, etc.) via MCP tools, with built-in login and MFA support.

Provides comprehensive food hierarchy and nutrition data through structured tools that enable searching foods, browsing categories, and retrieving detailed nutritional information from a MongoDB Atlas database.

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.

Enables scoring the WHO-5 Well-Being Index from five answers, returning a 0–100 score and a low, reduced, or normal band without providing a diagnosis.

Provides local MCP tools to query your own Xiaomi Mi Fitness health data (sleep, workouts, heart rate, etc.) stored in a local SQLite database, enabling AI assistants to access personal health records without exposing credentials.

Enables AI assistants to search Italian private healthcare services, clinics, and doctors, compare real-time availability, bookable times, and prices, and retrieve service preparation and pricing information, while leaving booking on cup24.it.

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.

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.

Enables querying the Swedish Food Agency's nutrition database to search foods, retrieve nutrient values, compare foods, and calculate recipe nutrition per serving.

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.

Provides SQL access to the ANSES Ciqual French food composition database with nutritional data for over 3,000 foods. Supports full-text search and bilingual queries for comprehensive nutrition analysis.

Enables AI agents to look up businesses, find free appointment slots, book, list and cancel appointments at salons, barbershops, nail and brow studios and clinics. Works read-only without a customer login by returning a pre-filled booking link, and can also run against a built-in demo with sample businesses.

Enables AI assistants to read your Strava training data and answer plain-language questions about activities, splits, and totals across sports like running, skiing, and hiking.

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.

Connects WHOOP fitness tracker data to AI assistants like Claude and ChatGPT, enabling natural language queries about recovery, sleep, strain, and trends.

Query your Apple Health data including sleep, heart rate, steps, workouts, and more by ingesting an exported XML archive into a local SQLite database.

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.

Bridges Suunto watch data to AI assistants like Claude, enabling natural language queries about workouts, sleep, and recovery.

MCP server for the Oura Ring API v2, enabling natural language queries about sleep, readiness, activity, heart rate, and more.

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.

Provides Claude Code with access to peer-reviewed medical information from MedlinePlus and StatPearls, and acts as an unlicensed diagnostic medical expert for educational purposes.

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.

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.

Enables AI agents to sync WHOOP recovery, sleep, workouts, cycles, and body-measurement data into a local Postgres database and query it through fast, offline-capable MCP tools without repeatedly hitting WHOOP API rate limits.

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.

A Model Context Protocol server that enables seamless interaction between LLM-based agents and Apple Health data, allowing users to query, analyze, and manage health records through natural language commands.

Provides local safety regulation, weather, and dining hygiene context tools for the ATLAS multi-agent safety evaluation system.

Exposes Strava training data to Claude for coaching, planning, and analysis via a read-only MCP server with OAuth and Docker support.

Enables AI assistants to access and modify a user's real GymTimer workout and nutrition data stored in private iCloud, allowing natural-language queries about training history and the creation of workout templates and meal plans.