Developers
Start Building with DisasterAWARE.
Integrate global disaster, severe weather, catastrophe, and impact intelligence into your applications.
DisasterAWARE provides developers and technology partners with access to enriched disaster intelligence through enterprise APIs, webhooks, historical datasets, geospatial services, and Model Context Protocol (MCP) servers.
Whether you're building an insurance analytics platform, a corporate security application, a supply chain monitoring solution, or an AI-powered risk assistant, DisasterAWARE offers flexible ways to incorporate authoritative hazard information into your products.
From real-time event monitoring to historical catastrophe analysis and AI-native intelligence, find the integration approach that fits your application.
Choose your intelligence. Select your integration method. Start building.
Get Started In Four Steps
From Evaluation to Integration.
Step 1 — Explore Available Intelligence
Identify the intelligence your application needs.
DisasterAWARE offers access to:
- •Real-Time Event Intelligence: Active disasters, severe weather warnings, observed hazards, and enriched event information.
- •Severe Storm Intelligence: Hail swaths, estimated hail sizes, damaging wind footprints, and tornado tracks.
- •Historical Catastrophe Intelligence: Enriched historical events, geographic footprints, severity, and available associated impacts.
- •Geospatial Intelligence: More than 300 layers covering hazards, weather, forecasts, infrastructure, population, and vulnerability.
- •OSINT & Operational Threats: Supported intelligence about scheduled events, civil unrest, labor strikes, and other human-induced disruptions.
- •AI-Native Intelligence: Supported MCP integrations for historical and live disaster information.
Step 2 — Select Your Integration Method
Choose how your application will access DisasterAWARE intelligence.
Depending on your requirements, supported options include REST APIs, webhooks, bulk historical data delivery, geospatial services, and MCP servers.
You can combine multiple integration methods within a single application.
Step 3 — Request Access
Contact our team to discuss your intended application, required datasets, and evaluation needs.
We'll help determine the appropriate access options and provide relevant technical information.
Step 4 — Connect & Build
Use the appropriate technical documentation, connection information, and credentials to integrate DisasterAWARE intelligence into your application.
For the Enterprise V2 API, start with our existing production API documentation.
Choose Your Integration Path
Multiple Ways to Access DisasterAWARE Intelligence.
Different applications require different approaches to data delivery and integration.
REST APIs — Retrieve Disaster Intelligence
DisasterAWARE's enterprise APIs provide structured access to supported hazard intelligence, including event attributes, geographic information, severity characteristics, and available supporting data.
The Enterprise V2 API delivers enriched hazard records designed to simplify integration and reduce the need for multiple requests to retrieve related intelligence.
- •Retrieve supported active disaster and severe weather events.
- •Access enriched hazard information and geographic attributes.
- •Incorporate available observed hazard footprints and severity information.
- •Connect disaster intelligence with your existing application workflows.
- •Support automated event retrieval and analysis.
- Best for:
- Risk intelligence platforms, insurance technology, corporate security, supply chain monitoring, and operational risk applications.
- Use REST APIs to:
Webhooks — Receive Hazard Updates Automatically
DisasterAWARE supports webhook delivery of hazard updates to configured customer endpoints.
Rather than relying exclusively on repeated API requests, your application can receive supported hazard records as they are delivered.
Webhook delivery is configured for eligible customer integrations. The Enterprise V2 documentation provides the maintained technical reference.
- •Receive hazard updates through your application's endpoint.
- •Trigger downstream processing when relevant hazard information arrives.
- •Update customer-facing maps, dashboards, and monitoring applications.
- •Incorporate disaster intelligence into event-driven workflows.
- •Support automated geographic exposure analysis.
- Best for:
- Event-driven applications, automated monitoring, risk alerts, and operational workflows.
- Use webhooks to:
Historical Catastrophe Data — Analyze Past Disasters
DisasterAWARE provides an enriched historical catastrophe database containing approximately 680,000 events across more than 30 hazard types.
Available information includes historical event attributes, geographic footprints, intensity information, event evolution, and associated impacts.
Supported data access options include bulk Parquet datasets delivered through S3, along with available metadata and query capabilities.
Historical coverage and completeness vary by hazard, geographic area, and time period.
- •Analyze historical disaster activity across geographic regions.
- •Investigate past hurricanes, earthquakes, floods, wildfires, and severe storms.
- •Evaluate available geographic footprints and event severity.
- •Support catastrophe model research and validation.
- •Incorporate historical disaster records into analytical applications.
- Best for:
- Catastrophe modeling, underwriting, historical event research, property risk analysis, and data engineering.
- Use historical intelligence to:
MCP Servers — Connect AI Applications to Disaster Intelligence
DisasterAWARE supports AI-native integration through Model Context Protocol (MCP) servers.
These integrations enable compatible AI applications to access supported disaster intelligence tools, including historical catastrophe information and available live hazard capabilities.
MCP tool availability, connection requirements, and supported operations depend on the service and access provided.
- •Connect compatible AI applications to disaster intelligence.
- •Investigate historical catastrophe activity through supported tools.
- •Retrieve available live hazard information.
- •Support geographic and event-based research.
- •Incorporate structured disaster intelligence into AI-powered workflows.
- Best for:
- AI-powered risk assistants, catastrophe research, natural-language disaster queries, and intelligent analytical applications.
- Use MCP integrations to:
Geospatial Services — Integrate Geographic Intelligence
DisasterAWARE provides more than 300 geospatial intelligence layers covering natural hazards, weather, forecasts, infrastructure, population, vulnerability, and geographic risk.
Available integration methods depend on the specific layer and service.
- •Display hazard and weather information on interactive maps.
- •Incorporate available raster and vector geographic datasets.
- •Explore geographic exposure and vulnerability information.
- •Combine DisasterAWARE intelligence with customer-supplied asset locations.
- •Support spatial analytics and risk visualization.
- Best for:
- GIS applications, mapping platforms, geographic risk visualization, and exposure analysis.
- Use geospatial intelligence to:
Understanding Disasteraware Data
More Than Event Notifications. Enriched Intelligence for Your Applications.
DisasterAWARE combines information from authoritative agencies, scientific models, remote sensing, and other supported sources into structured intelligence designed for integration.
Depending on the hazard type and dataset, available information may include:
Event Information
Hazard classification, event location, timing, source, and available event characteristics.
Warnings & Forecasts
Authoritative warnings, forecast information, and geographic areas where hazardous conditions may develop.
Observed Hazard Intelligence
Available hail swaths, damaging wind footprints, tornado tracks, wildfire detections, flood observations, earthquake shaking, and other hazard information.
Geographic Footprints & Severity
Available tracks, polygons, intensity surfaces, estimated footprints, and other geographic representations of hazard conditions.
Exposure & Associated Impacts
Available information about potentially exposed locations and reported consequences, including casualties, displacement, damage, and other impacts.
Historical Context
Enriched historical disaster records that support event investigation, catastrophe research, and geographic risk analysis.
- Important:
- Available fields, source coverage, geographic precision, update frequency, and historical completeness vary by hazard and dataset. Forecasts, observations, modeled estimates, potential exposure, and confirmed impacts represent different types of intelligence.
Find The Right Integration For Your Application
Built for Different Products, Workflows & Technical Requirements.
| **Your Application** | **Recommended Starting Point** | |:--:|----| | Live disaster monitoring | Event Intelligence API | | Automated hazard notifications | Webhooks | | Insurance claims and catastrophe analysis | Severe Storm APIs + Historical Intelligence | | Historical catastrophe research | Historical Data / MCP | | AI-powered disaster assistants | MCP Servers | | GIS and mapping platforms | Geospatial Intelligence Layers | | Supply chain risk monitoring | Event Intelligence API + OSINT | | Corporate security and GSOC platforms | Event Intelligence API + Webhooks | | Property exposure analysis | Hazard Footprints + Geographic Intelligence |
Many applications benefit from combining multiple DisasterAWARE capabilities.
For example, an insurance technology platform may use real-time event intelligence to monitor developing hazards, historical catastrophe data for portfolio analysis, and geographic footprints to identify potentially exposed properties.
Technical Resources
Explore Documentation, Data & Integration Options.
Enterprise V2 API Documentation
The maintained technical reference for DisasterAWARE's production V2 API, including available endpoints, response structures, and webhook information.
MCP Servers & AI Integration
Learn how DisasterAWARE's MCP integrations connect compatible AI applications with supported historical and live disaster intelligence.
Sample API Responses
Review representative hazard records and structured response examples to understand how DisasterAWARE intelligence can be incorporated into applications.
Data Samples
Explore representative historical catastrophe datasets, geographic hazard footprints, and available data formats.
Geospatial Intelligence Layers
Explore available geospatial datasets, integration options, and layer catalogs.
Geospatial Integration Guide
Access existing information about getting started with DisasterAWARE geospatial intelligence services.
Built For Technology Partners
One Intelligence Partner. Flexible Integration Options.
DisasterAWARE is designed to help software providers, technology platforms, and data partners incorporate global disaster intelligence into their own products.
Our approach supports:
Embedded Intelligence
Enhance existing applications with structured disaster and severe weather information.
Multiple Delivery Methods
Choose among supported APIs, webhooks, historical datasets, geospatial services, and MCP integrations.
Multi-Hazard Coverage
Access a broad range of natural disaster, severe weather, environmental, and supported human-induced threat information.
Geographic & Historical Depth
Connect live event information with available geographic footprints, historical catastrophe records, and associated impacts.
Product Expansion
Start with a focused dataset or integration and incorporate additional supported intelligence as your application evolves.
Partnership-Oriented Delivery
Work with DisasterAWARE to identify appropriate datasets, licensing arrangements, and integration approaches for your product.
Ready to Integrate DisasterAWARE?
Whether you're evaluating a real-time hazard API, historical catastrophe dataset, geospatial service, or MCP integration, DisasterAWARE can help you identify the right starting point. Explore our existing technical resources or contact our team to discuss your application, data requirements, and evaluation options.