Who this is for
Realtors and MLS operators
Surface home valuation estimates, track inventory velocity, and display local market trends on your listings platform
Real estate investors
Analyze property-level financials, monitor home price trajectories, and identify off-market opportunities at scale
Capital markets and portfolio teams
Model portfolio valuations, assess geographic concentration risk, and benchmark against secondary market indicators
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
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
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
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
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
- MCP server (AI-embedded)
- REST API (direct integration)
Best for: Teams building AI-powered real estate assistants, search copilots, or investment analysis toolsConnect 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: GATypical tool call sequence:
analytics-market_trends_tool→ retrieve market conditions for target geographyanalytics-hpi_forecast_tool→ get forward-looking price forecastclip-find_property_by_full_address→ resolve specific propertypc-characteristics_by_clips_tool→ get property-level details
Relevant capabilities
Get started
1
Define your analytics needs
Identify the geographies and metrics that matter to your business — listing trends, price forecasts, rental data, or property-level screening
2
Get credentials and authenticate
Obtain OAuth2 client credentials and get your first access token
3
Query a target market
Use the MCP inspector or the analytics tool reference to run your first market trend or HPI query against a ZIP code or CBSA of your choosing
4
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