About This Site
Cited geospatial data API for AI agents and physical-world decisions Mireye is a geospatial infrastructure platform that connects AI agents to authoritative physical-world and environmental data through one API and MCP server. It enables agents to ask location-based questions, geocode addresses, retrieve cited geographic fields, measure proximity and driving distances, and request new data fields. Responses include structured values, source attribution, source URLs, fetch timestamps, confidence scores, and typed refusals when data quality is insufficient. Mireye covers US geospatial data from sources such as USGS, FEMA, NOAA, USDA, EPA, EIA, FCC, Census, NREL, and other federal, county, open, and licensed datasets. It supports applications including data center siting, renewable energy development, insurance underwriting, commercial lending, mortgage diligence, land evaluation, and infrastructure planning.
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Key Features AI
Core Features
Cited physical-world and environmental data for US locations
API and MCP integration for AI agents
Natural-language location questions through /v1/ask
Address geocoding with stated accuracy and confidence
Parcel, county, census, elevation, flood, soil, utility, and infrastructure lookups
Batch field retrieval with source URLs, fetch timestamps, and confidence scores
Driving distance, proximity, nearest-infrastructure, screening, and labor-shed analysis
Field request workflow for data not yet available in the catalog
Support for Claude, ChatGPT, Gemini, Cursor, Grok, Copilot, DeepSeek, and custom agents
Typed refusals for low-confidence matches and unsupported requests
Advantages
Every returned value includes source attribution, a URL, fetch timestamp, and confidence level
Combines many authoritative geospatial and environmental sources in one API
Designed for direct integration with AI agents through an API and MCP server
Supports natural-language questions as well as structured data retrieval
Offers batch processing for many locations
Refuses weak or low-confidence matches instead of guessing
No overage billing; requests stop when the credit allowance is exhausted
Supports custom field requests when the catalog lacks required data
Useful presets for site selection, flood risk, terrain, utilities, solar, wind, and data centers
缺点：The main data catalog is limited to the United States
缺点：Drive-time analysis is the only feature explicitly covering both the US and Canada
缺点：Credits reset monthly and unused credits do not roll over
缺点：Usage pauses when the monthly allowance is reached
缺点：Parcel lookup is relatively expensive at 300 credits per successful match
缺点：Some data layers may not be real-time and freshness varies by source
缺点：Enterprise features, dedicated coverage, and SLAs require custom pricing
缺点：Field requests may require research and development before becoming available
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30-Day Click Trend
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