GDAL
Empowers AI agents to conduct GDAL-style geospatial analysis, offering catalog discovery, metadata intelligence, and raster/vector processing via Python-native libraries and natural language interaction.
Acerca de
GDAL is a production-ready Model Context Protocol (MCP) server that democratizes access to powerful GDAL-style geospatial operations through natural language. It's built for domain experts, abstracting away the complexities of command-line interfaces, programming, and system configuration. Leveraging Python-native libraries like Rasterio, GeoPandas, and PyProj, GDAL provides AI agents with robust capabilities including catalog discovery, metadata intelligence, and comprehensive raster/vector processing, all supported by built-in reasoning guidance and reference resources.
Características Principales
- Production-Ready MCP server for geospatial operations
- 5 Core Tools: `raster_info`, `raster_convert`, `raster_reproject`, `raster_stats`, `vector_info`
- 7 GitHub stars
- Python-Native Stack (Rasterio, PyProj, pyogrio, Shapely) without GDAL CLI dependency
- Type-Safe operations with Pydantic models and Workspace Security
- Resource Discovery, Metadata Intelligence, and Reference Library for AI agents
Casos de Uso
- Simplifying GDAL operations for domain experts through natural language queries
- Enabling conversational AI agents to perform complex geospatial data processing tasks
- Automating geospatial catalog discovery and metadata analysis for AI-driven workflows
