GIS MCP Server

Instructions

Implementation Reference

• src/gis_mcp/rasterio_functions.py:918-952 (handler)

  The handler function that implements the core logic of the raster_band_statistics tool. It reads the input raster, computes min, max, mean, and standard deviation for each band using rasterio and numpy, handling masked arrays for NoData values, and returns a dictionary with the statistics.

  def raster_band_statistics(
      source: str
  ) -> Dict[str, Any]:
      """
      Calculate min, max, mean, and std for each band of a raster.
  
      Parameters:
      - source: path to input raster (local or URL).
      """
      try:
          import numpy as np
          import rasterio
  
          src_path = os.path.expanduser(source.replace("`", ""))
          stats = {}
  
          with rasterio.open(src_path) as src:
              for i in range(1, src.count + 1):
                  band = src.read(i, masked=True)  # masked array handles NoData
                  stats[f"Band {i}"] = {
                      "min": float(band.min()),
                      "max": float(band.max()),
                      "mean": float(band.mean()),
                      "std": float(band.std())
                  }
  
          return {
              "status": "success",
              "statistics": stats,
              "message": f"Band-wise statistics computed successfully."
          }
  
      except Exception as e:
          raise ValueError(f"Failed to compute statistics: {e}")

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

  The raster_band_statistics tool is registered/listed as one of the available rasterio operations in this resource endpoint.

  @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"
          ]
      }