MCP server that lets Claude run Google Earth Engine
An MCP server that lets Claude run Google Earth Engine.
Ask Claude to build a cloud-free satellite image of anywhere on Earth, compute vegetation indices, pull statistics, or classify land cover, and it actually does it on Google's servers. geeflow is the connector that makes that work: a Model Context Protocol (MCP) server exposing Earth Engine as a set of typed tools, plus a code tool so Claude can run arbitrary Earth Engine Python when a task needs something custom.
Underneath the MCP server is a full Python toolkit (usable on its own via CLI or import), so anything an AI session does, a human can reproduce.
Through Claude (or any MCP client), geeflow can:
- Find data: search the Earth Engine catalog (880+ datasets) and read dataset metadata - Build imagery: cloud-free, harmonized composites for any place and any year since 1972. It picks the right satellite for the year (Landsat MSS through Sentinel-2), cloud masks, renames bands to one common scheme, and falls back to backup sensors or wider date windows when scenes are scarce - Analyse: spectral indices (NDVI, SAVI, EVI, NDMI, NBR, NDWI, NDBI, red-edge), per-region statistics, scene availability - See it: PNG thumbnail links so you and Claude can look at the result - Training data: auto-generate labeled polygons from land-cover products like ESA WorldCover - Classify: a full land-cover classification workflow with honest, leakage-safe accuracy (optional, see below) - Export: send results to Google Drive or an Earth Engine asset, and track the jobs - Anything else: an executecode tool runs arbitrary Earth Engine Py
From the project README.
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