Mireye
Provenance-tagged US geospatial data API for AI agents and underwriters.
If you need audit-ready geospatial data for US locations and you're comfortable with an API/MCP workflow, Mireye is a solid pick—the citations and confidence scores make it defensible in regulated settings. Skip it if you need global coverage, predictive analytics, or a plug-and-play GUI.
Verified 4d ago · liveness 48/100 · cite: rightaichoice.com/tools/mireye
- Insurance underwriters needing auditable, federal-source geospatial data for US properties
- Lenders and mortgage teams wanting cited flood, terrain, and hazard data for property assessments
- AI agents or developers building MCP-native geospatial tools for US use cases
- Renewable energy developers screening sites for solar, wind, or storage siting
- Users needing global coverage outside the US and territories
- Projects requiring real-time streaming data or historical time series
- Teams without technical ability to integrate REST APIs or MCP servers
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Skip Mireye if you need global coverage, real-time streaming, or a ready-to-use risk score—it's US-only, requires API integration, and deliberately doesn't offer proprietary risk scores.
Going past your monthly credits auto-recharges at $1.00 per 1,000 credits, which adds up at high volume unless you monitor usage.
Credit-based pricing fits small teams and cost-conscious developers with a generous free tier and $19/mo Build plan. Compared to other geospatial APIs that charge per-record with higher minimums, Mireye's transparent per-call credits offer flexibility, but heavy users may find the $1.00/1k overage rate less competitive than volume-based plans.
In short
Mireye — Provenance-tagged US geospatial data API for AI agents and underwriters. Best for Insurance underwriters needing auditable, federal-source geospatial data for US properties, Lenders and mortgage teams wanting cited flood, terrain, and hazard data for property assessments, AI agents or developers building MCP-native geospatial tools for US use cases. Free to start; paid plans from $19/mo.
What's new in Mireye
Checked 2 days agoAcross the latest 3 updates: 3 news mentions.
Do Parking Lots Have Solar Potential?
Research post assessing solar potential of US parking lots via Mireye API.
We Screened Every Meat Plant in America in One Afternoon
Screening of US meat plants for cold-chain fragility using Mireye data.
Site Selection Is Now Grid Selection: Screening Land for Data Centers
Data center site selection prioritizes power grid access; Mireye data supports screening.
What people actually say about Mireye — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
- +Provenance-tagged data with exact federal source citations.
- +Dual API endpoints: LLM-synthesized answers and raw field values.
- +MCP server integrates directly with Claude Desktop and Cursor.
- +207 fields across 7 layers covering terrain, land cover, climate, etc.
- +Partial failure reporting with retryable flag for unavailable fields.
- −No community reviews or testimonials to verify claims.
- −Pricing is opaque – no free tier or transparent cost breakdown.
- −Documentation is sparse and lacks troubleshooting examples.
- −Support channels are not publicly visible or easily accessible.
- −Retry limits on partial failures can block critical workflows.
- • No free tier means you must commit payment before testing data quality.
- • Retry failures may incur additional costs if charged per request.
- • Overage or rate-limit penalties are unstated.
Viability Score
How well maintained and how widely used is Mireye? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: August 2026
How we score →Key Features
- Natural language /v1/ask endpoint returns synthesized answers with inline citations
- Raw field /v1/fetch endpoint returns per-field values with provenance for batch jobs
- Address geocoding /v1/geocode with match confidence and candidate handling
- Canonical parcel lookup /v1/lookup for coordinates, addresses, and APNs with typed refusal
- Drive-time distance & matrix via /v1/proximity covering US and Canada
- MCP server for Claude Desktop, Cursor, and custom MCP agents
- 285 cited fields across 7 layers: terrain, land cover, built environment, utilities, parcels, climate, hazards
- 15 use-case presets: solar_siting, flood_risk, data_center_siting, wildfire_underwrite, and more
- Field request system: describe missing data, queue a build, poll with request_id
- Partial failure reporting with retryable flag for unavailable fields
- Public field catalog at GET /v1/meta/fields
- Multiple auth methods: bearer token, dashboard API token, device-flow login, or MCP OAuth
- Data from 85 authoritative sources: USGS, FEMA, NOAA, USDA, EPA, EIA, FCC, Census, and more
- Per-field citations with source, source_url, fetched_at, and confidence bucket
- Batch processing: send hundreds of locations in one call, one bad address doesn't fail the rest
About Mireye
Mireye is a US-centric geospatial data API engineered for AI agents and regulated professionals who need cited, auditable facts about places—not just estimates. It replaces the vague, timestamp-free answers you get from a general LLM with precise values backed by federal sources like USGS, FEMA, NOAA, and USDA. Every response includes source name, clickable URL, fetched timestamp, and a confidence bucket, so an auditor can trace exactly where each number came from. The core is a set of HTTP endpoints. POST /v1/ask answers natural-language questions about any US location with synthesized, cited answers. POST /v1/lookup resolves an address, APN, or coordinates into a canonical parcel with parcel ID, owner, and census codes, refusing matches that aren't confident enough. POST /v1/geocode handles address-to-coordinate resolution with confidence scoring, while POST /v1/fetch returns raw per-field values with provenance for batch jobs—one bad address won't fail the rest. A newer /v1/proximity endpoint adds drive-time distance, nearest-by-road screening, and labor-shed population calculations for both US and Canadian locations. A key feature is the MCP server, which exposes these endpoints as tools for Claude Desktop, Cursor, and other MCP-native agents. The catalog now covers 285 cited fields across layers like terrain, land cover, built environment, utilities, parcels, climate, and hazards, plus 15 use-case presets like solar_siting, flood_risk, and data_center_siting. A field-request system lets you describe missing data in plain language, and genuine gaps are queued as builds that benefit all future users. Mireye is credit-based, with a 5,000-credit free tier and paid plans starting at $19/month. Each call type costs a fixed number of credits—geocode at 1, fields at 1 each, ask at 10, lookup at 300, proximity at 12-plus per calculation. Coverage is US-focused (with Canada for drive-time), and every response includes a fetched_at timestamp so you always know what
Behind the Verdict
Mireye has quietly become the default answer for a narrow but urgent problem: giving AI agents and regulated workflows geospatial facts they can actually defend. The citation layer—source name, clickable URL, fetched timestamp, confidence bucket—is the whole ballgame. For an underwriter or a site-selection analyst, a number without a timestamp is just a rumor; Mireye turns every field into a footnote. That's why it's resonated with insurance, mortgage, and data-center desks rather than hobbyists. When should you pick it? When your work lives in the US, your risk is in the details of terrain, flood, utilities, and parcels, and your regulator or client might ask 'where did that come from?' Mireye's edge over a general LLM is that it won't confidently guess—it refuses low-confidence matches, which in a compliance setting is a feature, not a bug. The batch fetch endpoint is also quietly strong: send hundreds of locations at once, and one bad address doesn't sink the whole job. That's the kind of reliability that wins renewals. When should you pass? If you need global coverage outside the US and Canada (and even Canada gets only the drive-time endpoint), you're looking at the wrong tool. If your use case demands real-time streaming or historical time series, Mireye's snapshot model—freshness varies by layer, with a fetched_at timestamp—will frustrate you. And if you're not a developer or you don't have an MCP-capable agent setup, the REST API learning curve will bite. This is not a 'load a map and click' product. The closest alternative is a general geocoding API (like Google's) or a GIS platform (like Esri), but those don't give you provenance-rich, federal-sourced facts with confidence scores in a machine-readable format. Mireye's credit model is also more transparent
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Real-world workflow fit
Concrete scenarios for the personas Mireye actually fits — and what changes day-one when you adopt it.
You need to verify flood zone and wildfire risk for a property in Galveston, TX before issuing a policy.
Outcome: Use POST /v1/ask with a natural-language question; Mireye returns cited values from FEMA and USGS, with source URLs and fetched timestamps, so you can include them in your underwriting report.
You're building a chatbot for a real estate site that answers questions about any US address.
Outcome: Integrate the MCP server into your agent; it can call /v1/geocode and /v1/fetch to provide elevation, flood zone, and nearby hazards, with citations users can verify.
You're screening a site in Ashburn, VA for a new data center and need grid interconnect, flood risk, and slope data.
Outcome: Call POST /v1/fetch with the data_center_siting preset (90 fields) to get all needed values in one request, with provenance, at about 9¢ per screen.
Use Cases
- Underwrite property insurance by verifying flood zone, wildfire fuel load, and nearest power plant with federal citations.
- Assess mortgage risk by fetching parcel zoning, elevation, and proximity to utilities for a given coordinate.
- Site a solar farm using the solar_siting preset which bundles irradiance, land cover, and terrain data.
- Evaluate a data center location by pulling grid interconnect, flood risk, and wildfire hazard data.
- Build an AI agent that answers geospatial questions about any US address with verifiable sources.
- Automate compliance reporting by extracting and citing federal-source geospatial attributes for a portfolio of properties.
Models Under the Hood
as of 2026-08-23
Limitations
- Mireye covers only the United States, as stated in its documentation.
- Field requests are HTTP-only today; an MCP tool for them is planned.
- Coarse geocoding matches are refused rather than guessed.
- Requires technical integration via REST API or MCP.
as of 2026-08-12
Verification history
We have re-verified Mireye 5 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-checked, vendor evidence unchanged
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Mireye tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Free
$0/mo
Ideal for
Solo developer or hobbyist exploring geospatial AI with a small US focus, needing up to 5,000 credits a month for testing.
What this tier adds
Starts you off with 5,000 credits/month, 20 req/min, and 1 field request at signup; no extra credits.
Build
$19/mo
Ideal for
Freelancer or small startup with modest geospatial needs, wanting reliable access to 25,000 credits a month and email support.
What this tier adds
Increases credits to 25,000, rate limit to 60 req/min, adds email support and $1.00/1k extra credits.
Growth
$99/mo
Ideal for
Growing team with heavier API usage, needing 120,000 credits/month and higher rate limits, plus shared Slack support.
What this tier adds
Bumps credits to 120,000, rate limit to 300 req/min, adds 3 monthly field requests and shared Slack channel.
Enterprise
Custom
Ideal for
Large organizations with sustained volume, needing custom SLAs, dedicated market coverage, and priority support.
What this tier adds
Offers custom SLAs/SLOs, dedicated market coverage, and volume pricing, with direct access to the team.
Where the pricing makes sense
The company stage and team size where Mireye's pricing actually pencils out — and where peers do it cheaper.
Credit-based pricing fits small teams and cost-conscious developers with a generous free tier and $19/mo Build plan. Compared to other geospatial APIs that charge per-record with higher minimums, Mireye's transparent per-call credits offer flexibility, but heavy users may find the $1.00/1k overage rate less competitive than volume-based plans.
Setup time & first value
How long it actually takes to get something useful out of Mireye — broken out by persona, not the marketing-page minute.
For developers, get your first /v1/ask response in about 5 minutes using the Quickstart guide. Sign up, grab a bearer token, and call the endpoint. MCP integration with Claude Desktop or Cursor takes under 15 minutes following the docs.
Switching to or from Mireye
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From Excel-based data lookup: Any team currently manually querying FEMA, USGS, etc., can script Mireye to fetch fields in bulk, saving hours per property.
- ↗To a global geospatial provider: If you need non-US coverage, you'll need to move to a provider like Google Maps or Mapbox, but you'll lose the federal citations.
Integrations
Resources & Guides
Tutorials & Learning
Official links
Tools that pair well with Mireye
Common stack mates teams adopt alongside Mireye, with the specific reason each pairing earns its keep.
Featured Head-to-Head Comparisons
Mireye vs Presto Voice
If you run a QSR chain and need drive-thru automation with proven revenue lift, Presto Voice is the clear choice—it just landed Dairy Queen and offers up to 95% non-intervention. If you need auditable, provenance-tagged geospatial data for US coordinates, Mireye is your tool—perfect for underwriters and AI agents. These products serve entirely different domains, so the right pick depends on your business: order-taking or location intelligence.
Mireye vs Truleo
These tools serve entirely different domains: Truleo is for law enforcement agencies drowning in siloed data, offering automated lead generation and report writing, while Mireye is for insurance underwriters and lenders needing auditable geospatial data. Choose based on your sector – not comparable head-to-head.
Mireye vs Screenplayiq
Choose ScreenplayIQ if you're a film professional needing script marketability predictions and structural feedback. Choose Mireye if you require auditable geospatial data for US coordinates, particularly for insurance underwriting or site selection. They serve entirely different domains; no direct overlap.
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