An MCP server that integrates AI retrievals with NASA's Common Metadata Repository (CMR), allowing users to search NASA's catalog of Earth science datasets through natural language queries.
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.
An MCP server that connects AI agents to cloud-native geospatial data via STAC metadata and DuckDB with H3 spatial indexing, enabling zero-configuration SQL queries on terabyte-scale datasets over S3.
MCP server for interacting with Google Earth Engine, enabling geospatial analysis such as dataset visualization, statistics computation, and search via AI assistants.
MCP server for the Geopera geospatial data platform that enables AI agents to discover imagery, place and manage orders, and run analytics using the same API as other Geopera clients.
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.
