"Information about RAG (Retrieval-Augmented Generation) or rag-related topics" matching MCP servers:

Enables MCP hosts to query a curated traditional Chinese medicine wellness knowledge base, run constitution assessments, identify intake information gaps, and obtain rule-based safety checks with five-tier risk conclusions.

A comprehensive health coaching system that combines blood test analysis with evidence-based nutritional therapy recommendations, powered by Retrieval-Augmented Generation (RAG).

Enables querying a local health knowledge base with hybrid RAG (vector + FTS5) and exploring backlinks between notes.

Provides access to MedlinePlus consumer health information from NIH, enabling free-text search across health topics.

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.

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.

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 browsing the Ptitchef recipe category tree and reading its recipes without an API key or account.

Enables retrieval of InBody body composition data including profile, scan history, and full metrics via MCP tools.

MCP server for Cronometer nutrition tracking, enabling food diary management, nutrition data retrieval, food search, and biometric tracking via Cronometer's mobile REST API.

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.

Mock MCP server for pediatric CKD risk warning, enabling patient biochemical trend retrieval, deterministic risk rule evaluation, structured alert triggering, and clinical SOP lookup using simulated data.

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

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

MCP server for Cronometer nutrition tracking using the mobile API. Enables food logging, nutrition data retrieval, diary management, and fasting tracking.

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

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.

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.