Enables AI agents to query Earth observation data, satellite imagery, active fires, and weather via natural language, returning interactive maps and briefs.
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.
An MCP server for Earth Observation processing, exposing Rust-accelerated EO computation tools like spectral indices, change detection, and classification for AI agents.
A Python MCP server for discovering and analyzing Sentinel-2 L2A imagery, enabling AI agents to search scenes, check quality, and compute spectral indices like NDVI, NDWI, and NBR from remote COG windows.
A Python MCP server that provides unified access to satellite and geospatial data through natural language queries, with automatic place name geocoding and support for raster, vector, and Zarr formats.