wildfire-mcp-server

A Model Context Protocol (MCP) server for detecting, monitoring, and analyzing potential wildfires globally using multiple data sources including NASA FIRMS, OpenWeatherMap, and Google Earth Engine.

This MCP server provides AI assistants with tools to detect and analyze wildfire activity anywhere in the world by integrating real-time satellite data, weather forecasts, air pollution metrics, and geographical information. It's designed to help identify potential wildfires and assess their environmental impact.

• Fire Detection: Query NASA FIRMS (Fire Information for Resource Management System) for active fire hotspots
• Weather Forecasting: Get 5-day weather forecasts for specific locations
• Air Pollution Monitoring: Access current and historical air pollution data
• Reverse Geocoding: Convert coordinates to human-readable addresses
• Fire Fuel Assessment: Determine if a location contains potential wildfire fuel based on land cover data
• Customizable Filtering: Filter fires by radiative power, brightness temperature, and geographic boundaries

Configure API keys (if required):

• NASA FIRMS Map Key
• OpenWeatherMap API Key
• Google Earth Engine credentials (if applicable)

Get potential wildfires for a specific date using NASA FIRMS data.

Parameters:

• date (str, optional): Date in YYYY-MM-DD format. Defaults to current date.
• frp (float): Fire Radiative Power threshold (default: 1)
• bright_ti4 (float): Brightness temperature threshold (default: 50)
• in_iran (bool): If True, filters fires to only show those within Iran's borders (useful for Iran-specific monitoring)
• bounding_box (BoundingBox, optional): Custom bounding box to limit search area to any geographic region

Get the address for given coordinates.

Parameters:

• latitude (float): Latitude of the location
• longitude