One integration. 33 agencies.
Discover Census, BLS, HUD, Statistics Canada and more through a shared catalog and documented API, with source context retained.
THE US & CANADIAN PUBLIC DATA LIBRARY
US and Canadian public data, connected to the places that matter. Explore people, housing, businesses and geography. Let the Librarian show you where to start.
For developers, researchers, businesses and AI agents.
Measured Data API uptime · monitoring coverage available on Status
Today the Librarian takes a closer look at HMDA Mortgage Lending—what it contains, where it applies, and how to start exploring it.
Read the noteUse the source directly when it meets your needs. GeoAmCan brings public data from 33 agencies into a common API and geographic framework—so you can spend more time investigating places.
Discover Census, BLS, HUD, Statistics Canada and more through a shared catalog and documented API, with source context retained.
A shared geographic analysis framework for both countries. Native definitions, release periods and currencies stay explicit.
Our MCP server gives authorized AI clients dataset discovery and geographic tools. The Librarian explains what to use.
Explore MCP ↗Build drive-time areas around US and Canadian locations, then analyze supported data within them. Free-flow estimates; no live traffic.
Explore drive-time areas ↗published records / source cells
available datasets
public source agencies
geographic boundary records
Catalog verified November 7, 2026. Counts include statistical source cells, not unique people or businesses. Coverage varies by dataset, geography and release.
Explore population patterns, business clusters, commuting, housing and risk context. Switch a layer to see how a geographic question takes shape.
Use driving areas around a clinic, development site or community facility. US and Canadian origins are supported; road and analytical coverage vary.
Drive-time API ↗The map illustrates possible analyses. Animations are not measured results, computed routes or live traffic.
Explore the communities behind a market: population, age and household context.
Illustrative connections show how commuting data can inform location decisions. Not live traffic or measured routes.
Explore industry concentration and business counts across potential markets.
Put housing, permits and rent benchmarks together to understand a market’s context.
Connect published hazard context with the communities around it. These zones illustrate the workflow, not actual hazard boundaries.
Population, age, education and the communities behind the numbers.
Earnings, workforce characteristics, jobs and commuting.
Establishments, industry classifications and business locations.
Housing stock, household characteristics and construction.
The geographic framework for connecting facts to places.
Community health, environmental context and designated areas.
Sources include U.S. Census Bureau, Statistics Canada, BLS, BEA, HUD, FEMA, EPA and USDA.
Independent platform. No agency affiliation or endorsement.
You do not need to know a table name to begin. Tell the Librarian what you want to understand. It will identify relevant sources, methods and limitations.
Bring workforce, industry and population evidence into your next location decision.
Explore housing conditions and published designations, with eligibility limits kept explicit.
Find demographic, economic and community health evidence for your assessment.
Investigate potential demand, nearby clinics and the limits of national spending benchmarks.
Selecting a question fills the chat. Send it when you are ready. Public access includes up to 20 chats per day, subject to service availability.
Explore in conversation. Integrate through REST. Give your AI agent authorized access through our MCP server.
Fulton County, Georgia
90% confidence · ACS 5-year · 2020–2024
A survey estimate over five years, with its published margin of error. The label combines the variable label and universe from our table metadata.
Explore variable definitions ↗curl --get "https://api.geoamcan.com/v1/acs/observations" \
--data-urlencode "table=B19037" \
--data-urlencode "native_id=0500000US13121" \
--data-urlencode "variables=B19037_001" \
--data-urlencode "limit=1" \
-H "Authorization: Bearer $GEOAMCAN_API_KEY"{
"name": "Fulton County, Georgia",
"native_id": "0500000US13121",
"period": "2024",
"survey_window": "2020-2024",
"geography_vintage": "2024",
"metrics": {
"B19037_001": "462481"
},
"margins_of_error": {
"B19037_001": "1915"
},
"margin_of_error_confidence": 0.9
}U.S. Census Bureau · Captured 2026-11-04
Excerpt preserves response fields and value types.
Full response, request & label metadata ↗
Every useful answer begins with the right source. Explore publication status, release periods, geographic coverage and attribution before bringing data into your work.
Tell us what you’re working on. We’ll follow up about API access, coverage and the right fit for your workload.
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