HTAG Analytics expands its API to 87 endpoints, leveraging open source H3 to deliver high-precision, AI-ready property data across Australia.
HTAG Analytics has expanded its developer API to 87 live endpoints, positioning it as the most comprehensive Australian property data API, covering more than 15,000 localities and all 537 Local Government Areas. The platform is accessible via REST API and Model Context Protocol (MCP), targeting developers, analysts, and proptech platforms.
At the core of this expansion is the integration of H3, an open-source hexagonal grid system developed by Uber. The API includes 26 H3-indexed spatial endpoints, enabling street-block level analysis, eliminating boundary bias, and introducing mathematically consistent spatial modelling. This marks a first for publicly accessible Australian property data APIs.
The platform spans seven domains, including market intelligence, spatial analysis, property-level valuation, geographic concordance, demographics, address tools, and macroeconomic indicators. A 14-endpoint geographic concordance engine allows bidirectional translation across SA2, SA3, SA4, GCCSA, LGA, suburb, postcode, and H3 systems, removing the need for custom crosswalk tables.
Across its 87 endpoints, the API delivers supply-demand metrics, growth cycles, historical trends, AVMs, environmental risk data, and socioeconomic indices.
Through MCP integration, the API supports real-time querying via AI tools such as Claude, Perplexity, and Manus AI. The company positions itself ahead of competitors including Cotality, citing broader coverage and Australia-specific granularity.
“The Cotality MCP launch validated the category we have been building for two years,” said Mat Djolic, founder of HTAG Analytics. “Every endpoint in our API was built for the way Australian property research actually works — suburb by suburb, cycle by cycle, with the geographic and socioeconomic nuance that generic international platforms do not carry.”
Since its April 2026 launch, the platform has onboarded over 100 developers, with active daily usage across multiple data categories.
