JordanGunn/gdal-mcp

Model Context Protocol server that packages GDAL-style geospatial workflows through Python-native libraries (Rasterio, GeoPandas, PyProj, etc.) to give AI agents catalog discovery, metadata intelligence, and raster/vector processing with built-in reasoning guidance and reference resources.

42
/ 100
Emerging

This tool helps geospatial professionals, scientists, and data analysts perform complex geospatial analysis using AI agents. It processes various geospatial data like satellite imagery and shapefiles, enabling operations such as reprojection, format conversion, and statistical analysis. The key output is not just processed data, but also a clear, documented explanation from the AI of why specific methodological choices (like resampling or coordinate systems) were made, ensuring scientifically sound and reproducible results.

Use this if you need an AI agent to perform geospatial data analysis and require it to explain and justify its methodological decisions for transparency, accuracy, and reproducibility.

Not ideal if you are looking for a simple, 'black-box' tool that executes geospatial commands without requiring an explicit reasoning or audit trail from the AI.

geospatial-analysis GIS remote-sensing cartography spatial-data-science
No Package No Dependents
Maintenance 10 / 25
Adoption 8 / 25
Maturity 15 / 25
Community 9 / 25

How are scores calculated?

Stars

56

Forks

4

Language

Python

License

MIT

Last pushed

Feb 20, 2026

Commits (30d)

0

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