Skip to main content
Glama
climate.py2.14 kB
import logging from pathlib import Path from typing import Optional, Dict, Any import cdsapi from ..mcp import gis_mcp logger = logging.getLogger(__name__) DEFAULT_PATH = Path(__file__).resolve().parent / "climate_data" @gis_mcp.resource("gis://operations/climate") def get_climate_operations() -> dict: """List available climate operations.""" return {"operations": ["download_climate_data"]} @gis_mcp.tool() def download_climate_data( variable: str, year: str, month: str, day: str, time: str = "12:00", dataset: str = "reanalysis-era5-single-levels", format: str = "netcdf", path: Optional[str] = None, ) -> Dict[str, Any]: """ Download climate data (ERA5 or other CDS datasets). Args: variable: e.g. "2m_temperature", "total_precipitation" year: e.g. "2024" month: "01".."12" day: "01".."31" time: Time of day (default: "12:00") dataset: CDS dataset name (default: "reanalysis-era5-single-levels") format: File format ("netcdf" or "grib") path: custom output folder (default: ./data/climate_data) Returns: {"status": "success", "file_path": "..."} or {"status": "error", "message": "..."} """ try: out_dir = Path(path) if path else DEFAULT_PATH out_dir.mkdir(parents=True, exist_ok=True) client = cdsapi.Client() file_path = out_dir / f"{dataset}_{variable}_{year}{month}{day}.{ 'nc' if format == 'netcdf' else 'grib'}" client.retrieve( dataset, { "variable": variable, "year": year, "month": month, "day": day, "time": time, "format": format, }, str(file_path), ) logger.info("Saved climate data %s for %s-%s-%s to %s", variable, year, month, day, file_path) return {"status": "success", "file_path": str(file_path)} except Exception as e: logger.exception("Failed to download climate data") return {"status": "error", "message": str(e)}

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/mahdin75/gis-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server