disaster-wire

npx add-mcp 'https://sukriramli-disaster-wire-mcp.hf.space/gradio_api/mcp'

Autonomous Global Disaster Intelligence Wire & MCP Server

An autonomous, 100% hands-off natural disaster intelligence wire engineered specifically for consumption by AI Agents, Large Language Models (LLMs), and automated RAG pipelines via the Model Context Protocol (MCP).

The pipeline monitors physical crisis telemetry (earthquakes, tsunamis, floods, tropical cyclones, volcanic eruptions, and severe weather), strips metaphorical news using semantic LLM triage, calculates spatial geohashes, cross-references proximity to critical supply chain infrastructure, and exposes structured tools for downstream AI assistants.

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🛠️ Model Context Protocol (MCP) Tools

This repository implements the Model Context Protocol (MCP) specification to provide real-time tool calling for Claude Desktop, Cursor, and custom agent runtimes.

1. list_active_disasters

Query active natural disaster events within the rolling 24–48 hour window with deterministic property filtering.

• Arguments:
  • event_type (string, optional): Filter by event category (earthquake, tsunami, flood, cyclone, wildfire, volcanic_eruption, severe_weather).
  • severity (string, optional): Filter by alert level (minor, moderate, severe, catastrophic).
  • country (string, optional): Filter by target jurisdiction (e.g., Japan, Philippines, United States).
  • limit (integer, optional): Max incidents to return (default: 10, max: 50).
• Returns: JSON object containing matched incidents, coordinates, geohashes, lifecycle phases, and recommended autonomous action playbooks.

2. get_disaster_by_id

Retrieve the full deterministic telemetry, impact stats, and source citations for a specific incident.

• Arguments:
  • event_id (string, required): The unique incident identifier (e.g., usgs_nc75001234, gdacs_1002341, or news_a1b2c3d4).
• Returns: Full JSON payload including raw sensor readings, depth, wind speed, casualty counts, and exposed infrastructure hubs.

3. find_disasters_near_coordinates

Performs geospatial radial queries using the Haversine great-circle distance formula to detect active threats around specific target locations.

• Arguments:
  • latitude (float, required): Target latitude between -90.0 and 90.0.
  • longitude (float, required): Target longitude between -180.0 and 180.0.
  • radius_km (float, optional): Radial search perimeter in kilometers (default: 500.0).
• Returns: Sorted list of active disasters ordered by proximity to the query coordinates, annotated with calculated distance in kilometers.

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📦 Client Configuration

Connecting Claude Desktop (Remote SSE)

Add the following to your claude_desktop_config.json:

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "disaster-wire": {
      "url": "[https://sukriramli-disaster-wire-mcp.hf.space/gradio_api/mcp/sse](https://sukriramli-disaster-wire-mcp.hf.space/gradio_api/mcp/sse)"
    }
  }
}