by JordanGunn · MCP Server · ★ 72
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
gdal-mcp MCP server exposing GDAL/Rasterio operations to AI agents, with a reflection middleware that requires structured justification before executing operations whose methodology matters (CRS choice, resampling method, query extent). Install Via uvx (recommended) Via Docker Local development Configure your MCP client Claude Desktop Add to (macOS: , Windows: , Linux: ): json { "mcpServers": { "gdal-mcp": { "command": "
| Stars | 72 |
| Forks | 7 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 77.5634965591893/100 |
| Open Issues | 1 |
| Last Updated | 2026-05-25 |
| Created | 2025-09-05 |
| Platforms | mcp, python |
| Est. Tokens | ~67k |
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gdal-mcp is 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 intelligen. It is categorized as a MCP Server with 72 GitHub stars.
gdal-mcp is primarily written in Python. It covers topics such as earth-observation, gdal, geospatial.
You can find installation instructions and usage details in the gdal-mcp GitHub repository at github.com/JordanGunn/gdal-mcp. The project has 72 stars and 7 forks, indicating an active community.
gdal-mcp is released under the MIT license, making it free to use and modify according to the license terms.
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