GIS MCP Server

Instructions

Implementation Reference

• src/gis_mcp/rasterio_functions.py:11-35 (registration)

  Resource function listing available rasterio operations, including "clip_raster_with_shapefile".
  @gis_mcp.resource("gis://operation/rasterio") def get_rasterio_operations() -> Dict[str, List[str]]: """List available rasterio operations.""" return { "operations": [ "metadata_raster", "get_raster_crs", "clip_raster_with_shapefile", "resample_raster", "reproject_raster", "weighted_band_sum", "concat_bands", "raster_algebra", "compute_ndvi", "raster_histogram", "tile_raster", "raster_band_statistics", "extract_band", "zonal_statistics", "reclassify_raster", "focal_statistics", "hillshade", "write_raster" ] }
• src/gis_mcp/rasterio_functions.py:359-442 (handler)

  The @gis_mcp.tool() decorated function that implements the clip_raster_with_shapefile logic: opens raster and shapefile, reprojects shapefile geometries to raster CRS if needed, applies rasterio.mask to clip, and writes the output raster.
  @gis_mcp.tool() def clip_raster_with_shapefile( raster_path_or_url: str, shapefile_path: str, destination: str ) -> Dict[str, Any]: """ Clip a raster dataset using polygons from a shapefile and write the result. Converts the shapefile's CRS to match the raster's CRS if they are different. Parameters: - raster_path_or_url: local path or HTTPS URL of the source raster. - shapefile_path: local filesystem path to a .shp file containing polygons. - destination: local path where the masked raster will be written. """ try: import numpy as np import rasterio import rasterio.mask from rasterio.warp import transform_geom import pyproj import fiona # Clean paths raster_clean = raster_path_or_url.replace("`", "") shp_clean = shapefile_path.replace("`", "") dst_clean = destination.replace("`", "") # Verify shapefile exists shp_path = os.path.expanduser(shp_clean) if not os.path.isfile(shp_path): raise FileNotFoundError(f"Shapefile not found at '{shp_path}'.") # Open the raster if raster_clean.lower().startswith("https://"): src = rasterio.open(raster_clean) else: src_path = os.path.expanduser(raster_clean) if not os.path.isfile(src_path): raise FileNotFoundError(f"Raster not found at '{src_path}'.") src = rasterio.open(src_path) raster_crs = src.crs # Get raster CRS # Read geometries from shapefile and check CRS with fiona.open(shp_path, "r") as shp: shapefile_crs = pyproj.CRS(shp.crs) # Get shapefile CRS shapes: List[Dict[str, Any]] = [feat["geometry"] for feat in shp] # Convert geometries to raster CRS if necessary if shapefile_crs != raster_crs: shapes = [transform_geom(str(shapefile_crs), str(raster_crs), shape) for shape in shapes] # Apply mask: crop to shapes and set outside pixels to zero out_image, out_transform = rasterio.mask.mask(src, shapes, crop=True) out_meta = src.meta.copy() src.close() # Update metadata for the masked output out_meta.update({ "driver": "GTiff", "height": out_image.shape[1], "width": out_image.shape[2], "transform": out_transform }) # Resolve destination path relative to storage dst_path = resolve_path(dst_clean, relative_to_storage=True) dst_path.parent.mkdir(parents=True, exist_ok=True) # Write the masked raster with rasterio.open(str(dst_path), "w", **out_meta) as dst: dst.write(out_image) return { "status": "success", "destination": str(dst_path), "message": f"Raster masked and saved to '{dst_path}'." } except Exception as e: print(f"Error: {e}") raise ValueError(f"Failed to mask raster: {e}")