By ATTOMLearning Objectives
- Understand why authoritative property data is the foundation under most real-estate AI
- Learn what a Model Context Protocol (MCP) server does and why it matters for AI agents
- Recognize the difference between a data platform and a valuation or analytics model
What Is ATTOM?
ATTOM Intelligence is the AI-native property-data platform from ATTOM Data Solutions, covering roughly 160 million US properties with thousands of discrete attributes spanning ownership, mortgage, tax, deed, foreclosure, boundary, and neighborhood data. The concrete problem it solves is foundational: nearly every real-estate model, valuation, or analytics product is only as good as the property data beneath it, and assembling clean, comprehensive, nationwide property data is expensive and hard. ATTOM aggregates and standardizes that data so lenders, insurers, investors, and proptech builders can pull authoritative facts about almost any US property through a single source.
ATTOM Data Solutions is a privately held property-data company that has spent years building its "data warehouse" of property information, covering the large majority of the US population across more than 3,000 counties. In 2026 it introduced ATTOM Intelligence — a framework defining how its data is structured, delivered, and applied for AI — and, notably, a public Model Context Protocol (MCP) server. The MCP server lets large language models and AI agents retrieve ATTOM property data directly, in a governed, standardized way, without a customer building custom integrations first.
💡Key Concept
MCP for property data: The Model Context Protocol (MCP) is an open standard that lets AI agents and large language models connect to external data sources in a consistent way. ATTOM's MCP server exposes its property data through that standard, so an AI agent can ask for facts about a property and receive governed, structured answers — turning a static database into something an autonomous AI workflow can query on its own.
✅Tip
Visit ATTOM: attomdata.com — for lenders, insurers, investors, and proptech developers; enterprise data licensing across API, bulk, and cloud delivery.
Core Capabilities
Nationwide property data warehouse
ATTOM maintains standardized data on roughly 160 million US properties with thousands of attributes and billions of rows of transaction-level history. This breadth lets a customer answer questions about ownership, value history, liens, and neighborhood context for almost any property in the country.
Flexible delivery — API, bulk, and cloud
The same data is available through APIs for real-time lookups, bulk files for large-scale ingestion, and cloud delivery through data platforms. Customers choose the delivery model that fits their engineering approach rather than being locked into one.
MCP server for AI agents
ATTOM's Model Context Protocol server is the AI-native hook: it lets AI agents and large language models consume ATTOM data directly through a standard interface, removing the custom-integration work that usually stands between raw data and an AI application.
Strengths
- Authoritative breadth: Coverage of roughly 160 million properties with thousands of attributes makes ATTOM a credible single source for nationwide property facts.
- AI-ready by design: Data is engineered for machine learning and analytics, and the MCP server exposes it to AI agents without bespoke plumbing.
- Delivery that fits the buyer: API, bulk, and cloud options suit real-time lookups, large ingests, and platform-native pipelines alike.
- Foundational, not siloed: Because it is a data layer, ATTOM can feed valuation models, risk tools, and analytics products across many use cases.
Limitations & Considerations
- It is data infrastructure, not a model. ATTOM supplies the facts; the AI-native delivery is the hook, but a customer still needs its own valuation, scoring, or analytics logic on top to turn data into decisions. The MCP server makes the data reachable, not self-interpreting.
- Data is only as fresh as its sources. Public-record data updates on jurisdiction-specific schedules, so some attributes can lag reality; users should confirm recency for time-sensitive decisions.
- Coverage and completeness vary by county. More than 3,000 counties are covered, but attribute depth differs by locality, and some fields are sparser in certain markets.
- Downstream use carries compliance duties. Property, mortgage, and neighborhood data used in lending or insurance decisions falls under fair-lending and consumer-protection rules, which remain the user's responsibility.
Best Use Cases
| Task | Why ATTOM |
|---|---|
| Building a real-estate AI or analytics app | AI-ready data on roughly 160 million properties via API, bulk, or cloud |
| Letting an AI agent query property facts | MCP server exposes the data directly to agents |
| Enriching a valuation or risk model | Thousands of attributes feed downstream models |
| Nationwide portfolio or market research | Standardized data across more than 3,000 counties |
Getting Started
- Contact ATTOM about the data attributes and coverage your use case needs.
- Choose a delivery method — API for real-time lookups, bulk for large ingests, or cloud for platform-native pipelines.
- To use the MCP server, connect your AI agent or large language model and test governed queries against sample properties.
- Layer your own valuation, scoring, or analytics logic on top, and confirm downstream use meets applicable compliance rules.
Key Takeaways
- ATTOM Intelligence is an AI-native property-data platform covering roughly 160 million US properties with thousands of attributes.
- Its Model Context Protocol (MCP) server lets AI agents consume the data directly, without custom integration.
- Data ships via API, bulk, and cloud, feeding valuation, risk, and analytics products downstream.
- It is data infrastructure more than a model — the AI-native delivery is the hook, but interpretation happens on top.
