"Health-related MCP servers or resources" matching MCP servers:

Read-only MCP server enabling natural language querying of personal health and cultural activity scores from the health.ojimpo.com dashboard via Claude.

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.

Enables AI agents to calculate BMI, BMR, TDEE, daily calorie needs, and macro nutrient splits using mQuickCalc's health formulas.

Lets Claude Code, Codex, and other AI assistants query locally collected Apple Health data, build weekly reports, check sync status, and log workouts or meals by hand.

Enables Claude to access Apple Health data (sleep, heart rate, steps, etc.) via a self-hosted MCP server, bypassing regional restrictions.

Enables AI agents to query personal health data collected by any wearable or phone fitness app through Android Health Connect or Apple Health, exposing read-only tools for metrics like heart rate, sleep stages, VO2 max, and body composition. It can run locally over USB with nothing stored, or be self-hosted on Cloudflare Workers with D1 to retain history beyond Health Connect's 30-day limit.

Enables authenticated owners to capture, review, correct, and export bodyweight and strength-training data through a ChatGPT interface, including bounded multi-image/multi-session batch review, typed metrics with explicit provenance, pending drafts requiring guarded confirmation, and reversible deletion.

Self-hosted MCP server that aggregates personal health data from Google Health, Oura, and Withings into a single, provider-attributed interface with configurable source of truth preferences.

An MCP server that connects AI clients to the Google Health API, enabling natural language queries about health and fitness data such as steps, sleep, heart rate, and exercise sessions.

A local-first MCP server that stores nutrition, biomarker, and wearable data in SQLite and exposes it as Model Context Protocol tools, enabling MCP-aware agents to log meals, query trends, and run correlations.

Exposes personal Garmin wellness data through MCP tools for accessing summary, sleep, HRV, heart rate, stress, body battery, and historical data.

Self-hosted MCP server that syncs Xiaomi fitness data to SQLite and provides authenticated tools to query health metrics (steps, sleep, HR, etc.) for AI assistants like Grok.

Gives Claude read access to wearable health data from Fitbit or Wear OS devices via the Google Health API, exposing tools for metrics like steps, heart rate, sleep, and workouts, plus a computed recovery score.

Private, read-only health data bridge that reads from Android Health Connect and exposes heart rate, steps, sleep, and other health metrics to ChatGPT via MCP tools.

Enables AI agents to query locally stored Samsung Health data—such as heart rate, sleep, steps, and workouts—through MCP tools for samples, daily summaries, and trend analysis while keeping everything on your own network.

A remote MCP server that allows trusted LLM assistants to read Google Health/Fitbit data and log nutrition, hydration, and body measurements via the Google Health API.

Exposes Fitbit sleep and recovery data to Claude via the Google Health API, with tools for sleep sessions, sleep summaries, recovery vitals, and raw health data queries.

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.

MCP server for the Google Health API: heart rate, activity, sleep, SpO2, HRV, ECG and irregular-rhythm notifications, read into a local SQLite cache for fast offline queries and trend analysis. OAuth 2.0 with automatic token refresh, incremental sync, a cache-only offline mode, and a doctor command that diagnoses a setup without spending quota.

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