Every place.
More possibility.
Property data APIs, MCP and AI agents.
Built for the products you create.
See the
whole picture.
Bring the property and the market
around it into the same workflow.
One intelligence layer.
Three ways to build.
Go straight to the data, connect your assistant, or start with a research workflow.
The data your
product needs.
Request market trends, address intelligence and geographic context in structured JSON.
/v1/reference/locality?name=Richmond&state_name=VICYour question.
Connected to the data.
Bring HtAG tools into an MCP-compatible assistant. Ask focused property questions and work with the underlying evidence.
“Compare two suburbs using the available price, rent and market-cycle data.”Connect your assistant
A useful place
to start.
Start a defined workflow for suburb analysis, comparison or market-cycle research. Review the sources and assumptions behind the result.
Every layer.
A little more
understanding.
From the address to the economy around it, bring the relevant context into view.
Explore the data catalogueUnderstand how a place is moving.
Prices, rents, supply, demand, growth cycles and risk indicators.
Browse endpointsStart with the place itself.
Standardise addresses, explore available property history and add local context.
Browse endpointsLook beyond the boundary.
Use H3 geographic cells with prices, rents, activity and environmental metrics.
Browse endpointsKnow the world around it.
Add Census, business activity, inflation and cash-rate context.
Browse endpointsConnect one geography to another.
Move between suburbs, LGAs, ABS geographies, postcodes and H3 cells.
Browse endpointsStart small.
Build something meaningful.
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Make it useful
Run a request, inspect the response and connect it to your workflow.
Follow the quickstart