GIS MCP Server

Instructions

Implementation Reference

• src/gis_mcp/rasterio_functions.py:443-535 (handler)

  The handler function decorated with @gis_mcp.tool() that implements the core logic for resampling a raster using rasterio, handling input validation, resampling with specified method and scale, and saving the output.
  @gis_mcp.tool() def resample_raster( source: str, scale_factor: float, resampling: str, destination: str ) -> Dict[str, Any]: """ Resample a raster dataset by a scale factor and save the result. Parameters: - source: local path or HTTPS URL of the source raster. - scale_factor: multiplicative factor for width/height (e.g., 0.5 to halve resolution, 2.0 to double). - resampling: resampling method name: "nearest", "bilinear", "cubic", etc. - destination: local filesystem path for the resampled raster. """ try: import numpy as np import rasterio from rasterio.enums import Resampling from rasterio.transform import Affine # Strip backticks if present src_clean = source.replace("`", "") dst_clean = destination.replace("`", "") # Open source (remote or local) if src_clean.lower().startswith("https://"): src = rasterio.open(src_clean) else: src_path = os.path.expanduser(src_clean) if not os.path.isfile(src_path): raise FileNotFoundError(f"Source raster not found at '{src_path}'.") src = rasterio.open(src_path) # Validate scale factor if scale_factor <= 0: raise ValueError("Scale factor must be positive.") # Compute new dimensions new_width = int(src.width * scale_factor) new_height = int(src.height * scale_factor) if new_width == 0 or new_height == 0: raise ValueError("Resulting raster dimensions are zero. Check scale_factor.") # Map resampling method string to Resampling enum resampling_enum = getattr(Resampling, resampling.lower(), Resampling.nearest) # Read and resample all bands data = src.read( out_shape=(src.count, new_height, new_width), resampling=resampling_enum ) # Validate resampled data if data is None or data.size == 0: raise ValueError("No data was resampled.") # Calculate the new transform to reflect the resampling new_transform = src.transform * Affine.scale( (src.width / new_width), (src.height / new_height) ) # Update profile profile = src.profile.copy() profile.update({ "height": new_height, "width": new_width, "transform": new_transform }) src.close() # Ensure destination directory exists dst_path = os.path.expanduser(dst_clean) os.makedirs(os.path.dirname(dst_path) or ".", exist_ok=True) # Write the resampled raster with rasterio.open(dst_path, "w", **profile) as dst: dst.write(data) return { "status": "success", "destination": str(dst_path), "message": f"Raster resampled by factor {scale_factor} using '{resampling}' and saved to '{dst_path}'." } except Exception as e: # Log error and raise for MCP to report logger.error(f"Error resampling raster '{source}': {e}") raise ValueError(f"Failed to resample raster: {e}")
• src/gis_mcp/rasterio_functions.py:11-35 (registration)

  Resource function that lists 'resample_raster' among available rasterio operations for discovery in the MCP system.
  @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" ] }