Mireye

Mireye is an infrastructure layer for AI agents that need reliable context about places and physical-world decisions. Through one API and an MCP server, agents can ask natural-language questions about a location, geocode US addresses, resolve places to canonical parcels, fetch typed fields, measure proximity, and request missing data fields. Responses are built for traceability: returned values include a source, source URL, fetch timestamp, and confidence level. The API can combine address resolution, field retrieval, and distance calculations into a replayable plan. Batch fetches support hundreds of locations, and invalid matches can be refused rather than guessed. Available data and operations cover terrain, elevation, flood risk, land cover, utilities, infrastructure, parcels, wildfire, wind, solar, storage, and other site-selection inputs. Proximity tools support driving calculations and nearest infrastructure across the United States and Canada; the main catalog covers US locations. Mireye is built for agents and applications used in data-center siting, renewable-energy screening, insurance underwriting, mortgage and title work, lending, and land diligence. Developers can test endpoints in the API playground and copy cURL, TypeScript, Python, or MCP configurations. Pricing is credit-based, with fixed costs per operation and no overage billing.