"World Health Organization" 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.

Exposes ESG/CSR data from Zei World to LLMs, enabling sector browsing, company search, ESG score comparison, and detailed evaluation criteria exploration through natural language.

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.

Exposes a connected-vehicle OBD-II/telematics platform to AI agents, enabling vehicle health scoring, live data queries, DTC decoding, maintenance prediction, and gated remote commands via a pluggable data layer.

Enables natural language querying of Korean public medical data (data.go.kr) through MCP clients like Claude, providing tools for searching hospitals, drugs, non-payment costs, disease statistics, and more.

Enables conversational AI to fetch live World Cup matches, standings, results, and generate journalist-style match summaries using MCP tools and prompts.

A professional-grade MCP server that enables AI assistants to monitor web services, APIs, and HTTP endpoints with enterprise-level security.

A minimal reference implementation of an MCP server that responds with "Hello, World" via Streamable HTTP. Serves as a baseline for integration testing and MCP client development with production-ready features including health checks, metrics, and containerized deployment.

Provides structured access to a World Cup SQLite database via MCP tools, enabling queries for tournaments, team histories, head-to-head matches, and player records.

Enables interaction with an explicit ARC-AGI-3 world model through typed operations for actor/rule editing, deterministic simulation, rendering, and observation comparison.

A minimal Model Context Protocol server in TypeScript that demonstrates MCP-compliant resources and tools for LLMs, featuring simple resources and a basic tool that echoes messages or returns greetings.

MCP server for read-only access to Xiaomi Mi Fitness shared family health data, enabling queries for family members, health summaries, and historical metrics via ChatGPT.

An MCP server that securely syncs and queries your health data from Apple Health, storing it in your own Supabase Postgres database and exposing tools for AI assistants to retrieve weight, calories, macros, and more.

Enables users to query Garmin health, activity, sleep, HRV, and training data through read-only MCP tools from ChatGPT or Codex.

Enables read-only access to Chinese FHIR electronic health records, including patient summaries, medication review context, record queries, and attachment reading, along with controlled CSV import and status tools.

A narrative graph engine that enables LLMs to generate, track, and mutate complex fictional worlds while maintaining consistency between factions, characters, and locations. It acts as a specialized RAG framework for storytelling, allowing models to manage thousands of entities without exceeding context limits.

A simple hello world MCP server with a greeting tool, deployable on Railway.

Self-hosted multi-user Google Health OAuth broker and read-only Agent API with remote MCP support. Enables users to connect their Google account and grant agents secure access to activity, sleep, heart, HRV, SpO2, and other health metrics via revocable per-token authentication.

Enables AI clients to securely access, query, and mutate normalized user-controlled health data (e.g., from Apple Health or Supabase) through a bounded set of MCP tools, with optional OAuth and sandboxed deployment.