"Hearth" matching MCP servers:

Integrates Taiwan-specific medical data including ICD-10 codes, FDA drug databases, and nutrition information into the Model Context Protocol. It enables AI models to query clinical guidelines, verify medical codes, and convert health data into FHIR R4 standardized formats.

MCP server for interacting with Google Earth Engine, enabling geospatial analysis such as dataset visualization, statistics computation, and search via AI assistants.

Integrates Taiwan health data and international medical standards, providing 28 MCP tools for diagnostics, drugs, lab tests, and clinical guidelines via FHIR R4.

Enables satellite imagery analysis through Google Earth Engine, allowing users to search datasets, calculate vegetation indices like NDVI, filter collections by location and date, and export imagery to cloud storage. Supports major satellite datasets including Sentinel-2, Landsat, and MODIS for applications like agriculture monitoring and deforestation tracking.

One-call Australian health and welfare data plumbing via AIHW — cited responses for practical analysis, not a data broker.

Enables interactive access to JAXA's satellite observation data (precipitation, land surface temperature, NDVI, elevation, soil moisture) via Claude, providing tools for point time series, dataset information, and area image generation.

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

An MCP server for querying and analyzing Apache Incubator podling health reports. It provides tools to list, search, and compare podling metrics across different time windows from Apache's health report Markdown files.

Metis — an open-source (AGPL-3.0), local-first MCP server / research companion. It answers from the user's own indexed PDF library with page-level citations (and flags what it can't find rather than inventing), keeps all data on the user's machine, and routes requests to 34 specialist agents.

Provides tools to search, download, and manage satellite imagery from all Copernicus Sentinel missions via the Copernicus Data Space ecosystem. It enables advanced geospatial queries, temporal coverage analysis, and automated data management for Earth observation tasks.

Enables AI agents to query verifiable physical-world ground truth for any point on Earth — water availability, seismic and space-weather hazard, ground stability, and resource indications — with every answer backed by a Bitcoin-anchored provenance record that can be independently verified. It also lets agents check whether an Earth-science hypothesis has already been tested, list documented nulls and retractions, and run bounded controlled tests that return UNTESTABLE rather than fabricate a result.

Enables discovery, analysis, and explanation of open satellite data through MCP, with support for STAC catalogs and NASA GIBS.

Enables AI agents to verify medical-record claims against synthetic FHIR evidence using a deterministic, non-AI verifier. Provides MCP tools for evidence retrieval, claim verification, and benchmark evaluation without requiring real patient data.