satellite-imagery-mcp
Related Servers
Alternatives to satellite-imagery-mcp
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityCmaintenanceEnables querying Sentinel-1/2, Landsat Collection 2, NAIP, and Copernicus DEM imagery by area and date, returning item IDs, footprints, cloud cover, and cloud-optimized GeoTIFF URLs.MIT
- AlicenseNot gradedqualityCmaintenanceEnables searching Microsoft Planetary Computer's STAC catalogue by area and date across open satellite and environmental collections, returning item IDs, footprints, dates, cloud cover, and per-band asset URLs.MIT
- AlicenseNot gradedqualityCmaintenanceEnables keyless search of the EU Copernicus Data Space catalogue, letting you find Sentinel-1/2/3/5P, DEM, land-cover, and burnt-area products by area and date and retrieve item ids, footprints, dates, and asset paths.MIT
- AlicenseAqualityBmaintenanceEnables 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.29Apache 2.0
- AlicenseNot gradedqualityCmaintenanceEnables retrieval of satellite vegetation statistics (NDVI) and searches of Sentinel-2 scene catalogs, returning results as JSON.MIT
- AlicenseBqualityDmaintenanceProvides 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.137LGPL 3.0
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: find_imagery searches and ranks scenes, while scene_assets retrieves file-level details for a specific scene. There is no overlap or ambiguity between them.
Both tool names follow a consistent verb_noun pattern (find_imagery, scene_assets), though scene_assets uses a noun-first structure rather than a verb. The pattern is still predictable and readable.
With only two tools, the server feels minimal but coherent: one for discovery and one for asset access. It is borderline because a satellite imagery workflow might expect additional operations like downloading or processing, but the two tools cover the core search-to-assets flow.
The server covers the essential discovery-to-asset pipeline, but lacks operations like direct download, scene metadata browsing, or comparison of multiple scenes. Agents can work around this by using the provided URLs, but the surface is thin for a full satellite imagery workflow.