> ## Documentation Index
> Fetch the complete documentation index at: https://develop.cotality.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Real estate

> Data and AI solutions for realtors, MLS operators, and real estate investors — track market trends, forecast home prices, and analyze investment opportunities.

Cotality's brokerage and investing solutions give real estate professionals and investors real-time access to the market intelligence, property data, and price forecasting tools they need to make faster, more confident decisions.

***

## Who this is for

<CardGroup cols={3}>
  <Card title="Realtors and MLS operators" icon="house">
    Surface home valuation estimates, track inventory velocity, and display local market trends on your listings platform
  </Card>

  <Card title="Real estate investors" icon="chart-line">
    Analyze property-level financials, monitor home price trajectories, and identify off-market opportunities at scale
  </Card>

  <Card title="Capital markets and portfolio teams" icon="building">
    Model portfolio valuations, assess geographic concentration risk, and benchmark against secondary market indicators
  </Card>
</CardGroup>

***

## Key use cases

### 1. Market health and listing activity

**Business problem:** Buyers, sellers, and agents need to understand current market conditions — how fast inventory is moving, where prices are trending, and how a specific market compares to regional or national benchmarks.

**With Cotality:** The market trend analytics tools return listing and market trend data across any ZIP code, county, CBSA, or state — covering median list price, days on market, inventory levels, sales volume, and list-to-sale price ratios.

**What you get:**

* Listing trend metrics: active listings, new listings, median list price, and median days on market
* Market trend metrics: closed sales volume, median sales price, and months of supply
* Geographic coverage: ZIP code, county, CBSA, and state levels

[View market trend analytics →](/mcp/market-trend-analytics/tools/analytics)

***

### 2. Home price forecasting

**Business problem:** Investors and portfolio managers need forward-looking price intelligence to underwrite acquisitions, model exit strategies, and stress-test portfolio performance under different macroeconomic scenarios.

**With Cotality:** The home price index (HPI) and HPI Forecast tools provide both historical price series and forward-looking forecasts — enabling scenario modeling, appreciation analysis, and portfolio stress-testing at the geographic level most relevant to your business.

**What you get:**

* Cotality HPI: index values and percent change by period
* HPI forecasts: projected appreciation or depreciation over a configurable forward window
* Multi-geography support: analyze at ZIP, county, CBSA, or state level simultaneously

[View HPI and forecast tools →](/mcp/market-trend-analytics/tools/analytics#analytics-hpi_tool)

***

### 3. Rental market analysis

**Business problem:** Real estate investors and operators evaluating single-family rental (SFR) or multifamily assets need rental market data to underwrite income assumptions and benchmark rent levels against current market conditions.

**With Cotality:** The rental trends tool provides median rental rates, year-over-year rent change, and vacancy trend signals for any geography — enabling acquisition underwriting, rent roll benchmarking, and market entry analysis.

**What you get:**

* Median rent by geography and period
* Year-over-year rent growth trends
* Comparative analysis across multiple markets in a single query

[View rental trends tool →](/mcp/market-trend-analytics/tools/analytics#analytics-rental_trends_tool)

***

### 4. Property search and screening

**Business problem:** Investors sourcing acquisition opportunities need to filter large sets of properties against specific investment criteria — size, age, value, land type — before committing to detailed due diligence.

**With Cotality:** Use the property characteristics tool to screen properties by physical attributes including square footage, year built, land use, lot size, and assessed value. Retrieve full parcel profiles for shortlisted properties to accelerate due diligence.

**What you get:**

* Filter criteria: `livingSquareFootage`, `actualYearBuilt`, `landDimensionAcresTotal`, `universalTotalValue`, and more
* Ownership and tax data for pipeline tracking
* Batch CLIP retrieval for portfolio-scale screening

[View property characteristics →](/mcp/property-data/tools/property-characteristics)

***

### 5. Embedding market data in consumer products

**Business problem:** MLS operators, brokerage portals, and listing platforms want to display live property valuations, neighborhood market stats, and price forecasts to consumers — but building and maintaining data feeds from multiple sources is costly and slow.

**With Cotality:** Integrate cotality's market analytics and property data directly into your product via MCP or REST API. Retrieve real-time stats for any listed property and its surrounding market — and surface them in listing cards, property detail pages, or neighborhood intelligence widgets.

**What you get:**

* Property-level data for individual listing display
* Market-level analytics for neighborhood context and comparison
* Standardized JSON responses that map cleanly to common frontend data models

***

## Integration paths

<Tabs>
  <Tab title="MCP server (AI-embedded)">
    **Best for:** Teams building AI-powered real estate assistants, search copilots, or investment analysis tools

    Connect an LLM or AI assistant to Cotality market and property data via MCP — enabling natural language queries like "What's the median home price trend in maricopa county over the last 12 months?"

    **Lifecycle:** <Badge color="green">GA</Badge>

    **Typical tool call sequence:**

    1. `analytics-market_trends_tool` → retrieve market conditions for target geography
    2. `analytics-hpi_forecast_tool` → get forward-looking price forecast
    3. `clip-find_property_by_full_address` → resolve specific property
    4. `pc-characteristics_by_clips_tool` → get property-level details

    [Get started with MCP →](/mcp/overview)
  </Tab>

  <Tab title="REST API (direct integration)">
    **Best for:** Teams embedding market data directly into product backends, data feeds, or analytical platforms

    Access listing trends, HPI, rental data, and property characteristics through standard REST endpoints.

    **Lifecycle:** <Badge color="green">GA</Badge>

    Key APIs for brokerage and investing use cases:

    * **Property API** — Property-level physical and ownership data
    * **Insight API** — Derived scores and valuations
    * **Spatial API** — Geographic and boundary data for market definition

    [Browse API reference →](/getting-started/overview#rest-apis)
  </Tab>
</Tabs>

***

## Relevant capabilities

| Capability                                                                              | What it provides                                            | Lifecycle                       |
| --------------------------------------------------------------------------------------- | ----------------------------------------------------------- | ------------------------------- |
| [CLIP tools](/mcp/property-data/tools/clip-tools)                                       | Address-to-CLIP resolution for any U.S. property            | <Badge color="green">GA</Badge> |
| [Property characteristics](/mcp/property-data/tools/property-characteristics)           | Physical, ownership, and tax data for individual properties | <Badge color="green">GA</Badge> |
| [Market trend analytics](/mcp/market-trend-analytics/tools/analytics)                   | Listing trends, market trends, and rental data by geography | <Badge color="green">GA</Badge> |
| [HPI and HPI forecasts](/mcp/market-trend-analytics/tools/analytics#analytics-hpi_tool) | Historical home price index and forward-looking forecasts   | <Badge color="green">GA</Badge> |

***

## Get started

<Steps>
  <Step title="Define your analytics needs">
    Identify the geographies and metrics that matter to your business — listing trends, price forecasts, rental data, or property-level screening
  </Step>

  <Step title="Get credentials and authenticate">
    Obtain OAuth2 client credentials and [get your first access token](/mcp/authentication)
  </Step>

  <Step title="Query a target market">
    Use the [MCP inspector](/mcp/quickstart) or the analytics tool reference to run your first market trend or HPI query against a ZIP code or CBSA of your choosing
  </Step>

  <Step title="Integrate into your product">
    Connect via MCP for AI-embedded or assistant use cases, or via REST API to feed data into your platform backend or analytics pipeline
  </Step>
</Steps>