DaedalMap
Organized cross domain geographical data
Details
- Target Audience
- AI DevelopersData ScientistsResearchers
- Pricing
- Freemium from $0.01
About DaedalMap
DaedalMap is a geographic data system for developers and AI agents. It gives you one MCP and API surface for organized datasets that would otherwise be scattered across different government, research, and disaster sources. The main goal is to make place-based data easier to discover, compare, and use. Instead of stitching together raw upstream APIs one by one, you can browse maintained packs, inspect pack metadata, and run structured queries against a shared geography model built around stable loc_id identifiers. Today the platform includes disaster, government, and research-oriented data such as earthquakes, tsunamis, hurricanes, volcanoes, currencies, UN SDG indicators, and World Factbook coverage. Some packs are free to explore and query, while paid lanes use x402 on Base/USDC. DaedalMap is designed for: AI agents that need a clean remote MCP or HTTP data surface developers building geographic or research workflows analysts who want structured, place-aware data without starting from raw GIS plumbing Start with the agent docs, inspect the catalog, pick a pack, and make your first call.
Product Insights
DaedalMap provides a unified MCP and API surface for accessing cross-domain geographical datasets from government and research sources. It simplifies data integration for AI agents and developers through a shared geography model and stable identifiers.
- Unified access to fragmented datasets including disaster, government, and research sources.
- Native MCP and HTTP support designed specifically for AI agent integration.
- Uses a shared geography model with stable loc-id identifiers for data consistency.
- Flexible freemium pricing with paid data lanes starting at 0.01 USD via Base/USDC.
Ideal for: AI Developers, Data Scientists, and Researchers who require structured, place-aware data for automated workflows and geographic analysis.
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Comments (1)
Come try our organized datasets, you can easily explore natural disasters, government data like currencies and SDG data metrics, and compare them via the loc_id system!