open-earth-mcp
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Alternatives to open-earth-mcp
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Related Servers
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- AlicenseAqualityAmaintenanceEnables 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.2915Apache 2.0
- AlicenseNot gradedqualityDmaintenanceEnables AI assistants to access free, open agronomic data for field briefings, spray windows, water balance, pest pressure, and more, using only public data sources without API keys.1MIT
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- AlicenseAqualityBmaintenanceEnables AI coding agents to score any geographic coordinate for ecological and agricultural land suitability by analyzing satellite and climate data, returning a weighted score with per-metric breakdowns for vegetation, water, terrain, and more.133 PyPIMIT
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TDQS
Scored across 6 tools
Each tool has a distinct purpose: scene search, NDVI time series, land cover, elevation, area report, and verification. The only mild overlap is area_summary, which composites land_cover/elevation/NDVI outputs, but its description clearly frames it as a small-box quick report, distinguishing it from the point-based tools.
All names are snake_case, but conventions are mixed: some are verb_noun (search_imagery, verify) and others are bare nouns (land_cover, elevation, ndvi_timeseries, area_summary). Readable but not a predictable pattern.
Six tools is well-scoped for an Earth-observation analysis server; each tool covers a distinct analysis primitive with no filler.
Core workflows—scene discovery, NDVI, land cover, elevation, summary, and verification—are covered. However, search_imagery returns scene IDs without any tool to fetch actual assets/pixels or download URLs, which is a notable gap for an imagery server, though analysis workflows are not blocked.