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

MCP server that demonstrates the Resources feature by exposing static and dynamic resources, including contact data and personalized greetings, through MCP.

Two self-hosted MCP servers: manage a local model machine (Ollama pull/switch, LoRA training) and bridge to local Ollama/vLLM for pure language processing tasks (writing, summarizing, classifying, extraction) without giving the calling agent tools or file access.

MCP server for the Swiss Federal Office of Public Health Infectious Disease Dashboard, providing access to epidemiological surveillance data for 51 pathogens across Switzerland, including influenza, COVID-19, measles, and wastewater surveillance.

MCP server for AI agent deployment health — gateway status, CPU/memory/swap, recent errors from journalctl/dmesg, skill registry integrity, upgrade outcomes, cron + disk usage. Each component gets HEALTHY/DEGRADED/CRITICAL classification with overall rollup.

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 securely read and analyze your Google Health data from Fitbit, Pixel Watch, and Health Connect, providing baseline-aware insights, readiness scores, trends, and anomalies while keeping data local and read-only.

MCP server for Obsidian vault structural health checks. Find broken wikilinks, orphaned notes, and missing frontmatter, with optional auto-repair.

An MCP server for auditing automation health, finding failures, stale logs, and non-functional endpoints that report success while quietly failing.

Enables users to store and query their own medical data—labs, medications, diagnoses, wearables, and food logs—in a local Postgres database and interact with it through any MCP client, with deterministic safety checks.

Local-first MCP server that reads Apple Health export files (export.xml/zip) and exposes activity, sleep, HRV, and workout data to AI agents, keeping all data on your machine.

A Claude-compatible MCP server that exposes health-domain tools over 100% synthetic data, built with security and compliance in mind.

Enables agents to locally analyze Huawei Health export data, retrieve activity summaries, tracks, samples, and health context, and generate structured report evidence with optional environmental data.

An MCP server that performs comprehensive health checks on project dependencies for JavaScript and Python projects, detecting outdated packages and fetching changelogs.

Read your Samsung Health CSV/ZIP exports — activity, sleep, heart, stress — locally. It is a local-first MCP server that keeps your tokens on your machine.

MCP servers for quantitative trading: live trading signals, market data, NAV history, portfolio management with dual-track (AUTO/MANUAL) performance comparison. Supports both stdio and Streamable HTTP transport.

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.

A local-first MCP server that enables AI agents to read user-authorized Google Health API v4 data from Fitbit, Pixel Watch, and partners via OAuth, with tokens never leaving the machine.

A workspace of six MCP servers—grounded-cv (hybrid RAG with citations), repo-intel (GitHub repo intelligence), web-research (safe web search/extraction), ats-jobs (unified ATS job boards), outcome-ledger (durable task ledger), and coding-workflows (code review & planning)—purpose-built for agentic hiring evaluations.

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.