Enables AI agents to query Earth observation data, satellite imagery, active fires, and weather via natural language, returning interactive maps and briefs.
Enables AI agents to autonomously discover, stream, and compute satellite analytics from free government Earth observation archives. Provides tools for STAC search, spectral indices, elevation profiles, SAR water detection, and sandboxed geospatial scripting.
Enables AI agents to autonomously discover, stream, and compute satellite analytics from free government Earth-observation catalogs such as Sentinel-2, Landsat, and Copernicus DEM, with zero API keys or configuration. It supports place-name geocoding, STAC scene search, cloud-native COG streaming for spectral indices, elevation profiles, SAR flood detection, and sandboxed custom geospatial scripts.
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.
A standalone Model Context Protocol server that lets AI clients search satellite scenes, fetch weather and climate series, query geographic layers, and compute vegetation indices and gradual-pattern analyses over environmental time series, returning structured results with source and limit metadata. It exposes 16 tools over stdio, streamable HTTP or legacy SSE and runs its own data retrieval and calculations.