Market and trend analytics - Cotality developer portal

Data capabilities:

Domain	Key metrics	Use cases
Listing trends	Active listings, new listings, median list price, days on market, list-to-sale price ratio	Inventory monitoring, pricing strategy, buyer demand signals
Market trends	Closed sales volume, median sales price, months of supply, sale-to-list ratio	Market health assessment, investment underwriting, risk/reward analysis
Rental trends	Median rental rate, year-over-year rent change	SFR acquisition underwriting, rent roll benchmarking, market entry analysis
HPI	Cotality Home Price Index value, month-over-month and year-over-year percent change	Portfolio valuation, appraisal benchmarking, collateral monitoring
HPI Forecasts	Projected appreciation or depreciation over a forward window	Acquisition modeling, exit strategy analysis, portfolio stress-testing

Data scope:

Attribute	Value
Input	Shared `AnalyticsFilter` — `geography_filter` (required) + `time_range` (optional)
Output	Common response envelope — `success`, `data`, `count`, `messages`
Geographic granularity	ZIP code (`zip_code`), county FIPS (`county_fips_code`), CBSA (`cbsa_code`), state (`state` / `state_id`)
Update frequency	Monthly (confirm exact lag with data team)
Historical depth	`[CONFIRM WITH DATA TEAM — e.g., available from 2000]`
Exclusions	US residential real estate only — commercial properties are not included

Shared input: `AnalyticsFilter`

All five analytics tools accept a single required parameter — analytics_filter — containing an AnalyticsFilter object.

`AnalyticsFilter`

Field	Type	Required	Description
`geography_filter`	`AnalyticsGeographyFilter`	Yes	Geography filter criteria
`time_range`	`TimeRange`	No	Time range filter — omit entirely to retrieve the latest available data

`AnalyticsGeographyFilter`

Field	Type	Required	Description
`geography_type`	`string` (enum)	Yes	Geography level to query (see Geography types)
`geography_type_values`	`array[string]`	Yes	One or more geography values to include in the query

Geography types

All geography_type values must be lowercase.

Value	Format	Example
`zip_code`	5-digit ZIP	`"90210"`
`county_fips_code`	5-digit FIPS	`"06037"`
`cbsa_code`	CBSA / metro code	`"31080"`
`state`	2-letter abbreviation	`"CA"`
`state_id`	Numeric state ID	`"06"`

geography_type_values accepts a list, so a single call can retrieve results for multiple geographies simultaneously (e.g., ["06037", "06059", "06065"]).

`TimeRange`

If time_range is provided, both from and to are required. Do not pass a partial object — omit time_range entirely to retrieve the latest data.

Field	Type	Required	Description
`from`	`YearMonth`	Yes (when `time_range` is present)	Start of the date range
`to`	`YearMonth`	Yes (when `time_range` is present)	End of the date range

`YearMonth`

Field	Type	Required	Description
`year`	`integer`	Yes	4-digit year (e.g., `2024`)
`month`	`integer`	Yes	Month, 1–12

Example filter

{
  "geography_filter": {
    "geography_type": "cbsa_code",
    "geography_type_values": ["31080"]
  },
  "time_range": {
    "from": { "year": 2024, "month": 1 },
    "to": { "year": 2024, "month": 12 }
  }
}

Response envelope

All five tools return the same top-level envelope. All four fields are always present in every response.

Field	Type	Description
`success`	`boolean`	Whether the request completed successfully
`data`	`array[object]`	Wrapper containing an `analytics` array — structure varies per tool (see each tool’s output schema)
`count`	`integer`	Number of records
`messages`	`array[string]`	Informational or warning messages

The data array contains a wrapper object with an analytics array. Each element in analytics groups results by geography and includes geographyType, geographyTypeValue, and a tool-specific data container (trends for the three trend tools, indices for the two HPI tools).

Do not assume response ordering. Always match results by reading the geographyType and geographyTypeValue fields on each result object, not by position.

Shared geography response fields

Every tool’s trend or index record includes the following geography and period fields. All fields are optional, nullable, and default to null.

Field	Type	Description
`cbsaCode`	`string`	CBSA code for the requested geography
`cbsaName`	`string`	CBSA name
`countyFipsCode`	`string`	5-digit county FIPS code
`countyName`	`string`	County name
`dataPeriod`	`string`	Cotality-assigned period identifier
`state`	`string`	Two-letter state abbreviation
`stateName`	`string`	Full state name
`stateId`	`string`	Two-digit state FIPS code
`yearMonth`	`integer`	Year and month in `YYYYMM` format
`zipCode`	`string`	5-digit ZIP code

Reading numeric values

Analytics fields use consistent numeric conventions:

Format	Convention	Example
Prices	Raw dollar value	`762000` = $762,000
Rates and shares	Decimal fraction	`0.048` = 4.8%
Index values	Base year 2000 = 100	`412.3` = 312.3% above baseline
Counts	Integer	`4821` = 4,821 transactions
Percentile ranges	5th / 95th in field names	`rentMin` / `rentMax` = 5th and 95th percentile

`pa-analytics_listing_trends_tool`

Retrieve property listing trends data for analyzing inventory levels, pricing, and market velocity in the residential real estate market. When to use:

Monitoring new listings, pending sales, closed sales, or delisted properties
Analyzing list prices, price reductions, or asking prices
Tracking days on market, time to sell, or listing duration
Evaluating market velocity, buyer/seller market indicators, or months of supply

Examples:

“How many active listings are there in Los Angeles County?”
“What is the median days on market for sold listings in California?”
“Show me buyer vs seller market indicators for CBSA 31080”

Input schema

All analytics tools accept the shared AnalyticsFilter input.

Parameter	Type	Required	Description
`analytics_filter`	`AnalyticsFilter`	Yes	Geography and optional time range filter

Example request

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "pa-analytics_listing_trends_tool",
    "arguments": {
      "analytics_filter": {
        "geography_filter": {
          "geography_type": "state",
          "geography_type_values": ["CA"]
        },
        "time_range": {
          "from": { "year": 2024, "month": 1 },
          "to": { "year": 2024, "month": 12 }
        }
      }
    }
  }
}

Output schema

The analytics array contains elements with geographyType, geographyTypeValue, and a trends.listingTrends array. Each listingTrends record includes the shared geography fields plus the fields below. All fields are optional, nullable, and default to null.

Field	Type	Description
`marketVelocity`	`number`	Active listings at month-end ÷ 12-month moving average of sold listings
`activeListings`	`ActiveListings`	Active inventory metrics
`allListings`	`AllListings`	Aggregate statistics across all listing statuses
`closedListings`	`ClosedListings`	Listings that closed (sold + delisted) during the month
`delisted`	`Delisted`	Listings removed without selling (cancellations, expirations, withdrawals)
`marketIndicator`	`MarketIndicator`	Buyer/seller market balance scores
`newListings`	`NewListings`	Fresh inventory entering the market
`pendingListings`	`PendingListings`	Listings under contract
`soldListings`	`SoldListings`	Completed sale transactions

`ActiveListings`

All fields are optional, nullable, and default to null.

Field	Type	Description
`inventoryCount`	`integer`	Number of listings active at month-end
`inventoryCountChangeFromPriorMonth`	`number`	Month-over-month change in active inventory count
`inventoryCountFiveYearMonthlyMean`	`number`	Five-year monthly average of active inventory count
`listPriceMean`	`integer`	Mean current list price for active listings
`listPriceMedian`	`number`	Median current list price for active listings
`listPriceStandardDeviation`	`number`	Standard deviation of current list price for active listings
`domMean`	`number`	Mean standard days on market for active listings
`domMedian`	`number`	Median standard days on market for active listings
`domStandardDeviation`	`number`	Standard deviation of standard DOM for active listings
`cumulativeDomMean`	`number`	Mean cumulative DOM for active listings (re-opened listings within 30 days count as one)
`cumulativeDomMedian`	`number`	Median cumulative DOM for active listings
`cumulativeDomStandardDeviation`	`number`	Standard deviation of cumulative DOM for active listings
`monthsSupply`	`number`	Active listings ÷ 12-month moving average of sold listings

`AllListings`

Statistics across all listing statuses (active, pending, and closed). All fields are optional, nullable, and default to null.

Field	Type	Description
`inventoryCount`	integer	Total listings in the month across active, pending, and closed statuses (each listing counted once)
`listPriceMean`	number	Mean current list price
`listPriceMedian`	number	Median current list price
`listPrice25thPercentile`	number	25th percentile of current list price
`listPrice75thPercentile`	number	75th percentile of current list price
`listPriceStandardDeviation`	number	Standard deviation of current list price
`domMean`	number	Mean standard DOM
`domMedian`	number	Median standard DOM
`dom25thPercentile`	number	25th percentile of standard DOM
`dom75thPercentile`	number	75th percentile of standard DOM
`domStandardDeviation`	number	Standard deviation of standard DOM
`cumulativeDomMean`	number	Mean cumulative DOM
`cumulativeDomMedian`	number	Median cumulative DOM
`cumulativeDom25thPercentile`	number	25th percentile of cumulative DOM
`cumulativeDom75thPercentile`	number	75th percentile of cumulative DOM
`cumulativeDomStandardDeviation`	number	Standard deviation of cumulative DOM
`listPricePercentChangeMean`	number	Mean percent change from original to current list price
`listPricePercentChangeMedian`	number	Median percent change from original to current list price
`listPricePercentChange25thPercentile`	number	25th percentile of list price percent change
`listPricePercentChange75thPercentile`	number	75th percentile of list price percent change
`listPricePercentChangeStandardDeviation`	number	Standard deviation of list price percent change
`listPricePercentChangeMeanChangeFromPriorMonth`	number	Mean list price percent change — month-over-month delta
`listPricePercentChangeMeanChangeFromPriorYear`	number	Mean list price percent change — year-over-year delta
`listPricePercentChangeMeanFiveYearMonthlyMean`	number	Mean list price percent change — five-year monthly average
`listPricePercentChangeMedianChangeFromPriorMonth`	number	Median list price percent change — month-over-month delta
`listPricePercentChangeMedianChangeFromPriorYear`	number	Median list price percent change — year-over-year delta
`listPricePercentChangeMedianFiveYearMonthlyMedian`	number	Median list price percent change — five-year monthly median

`ClosedListings`

Listings that closed during the month, including both sold and delisted (cancellations, expirations, withdrawals). All fields are optional, nullable, and default to null.

Field	Type	Description
`inventoryCount`	integer	Number of listings that closed during the month
`listPriceMean`	number	Mean current list price at time of close
`listPriceMedian`	number	Median current list price at time of close
`listPriceStandardDeviation`	number	Standard deviation of current list price at time of close
`domMean`	number	Mean standard DOM
`domMedian`	number	Median standard DOM
`domStandardDeviation`	number	Standard deviation of standard DOM
`cumulativeDomMean`	number	Mean cumulative DOM
`cumulativeDomMedian`	number	Median cumulative DOM
`cumulativeDomStandardDeviation`	number	Standard deviation of cumulative DOM
`cumulativeDomMeanChangeFromPriorMonth`	number	Mean cumulative DOM — month-over-month delta
`cumulativeDomMeanFiveYearMonthlyMean`	number	Mean cumulative DOM — five-year monthly average
`cumulativeDomMedianChangeFromPriorMonth`	number	Median cumulative DOM — month-over-month delta
`cumulativeDomMedianFiveYearMonthlyMedian`	number	Median cumulative DOM — five-year monthly median
`listPricePercentChangeMean`	number	Mean percent change from original to current list price
`listPricePercentChangeMedian`	number	Median percent change from original to current list price
`listPricePercentChangeStandardDeviation`	number	Standard deviation of list price percent change
`listPricePercentChangeMeanChangeFromPriorMonth`	number	Mean list price percent change — month-over-month delta
`listPricePercentChangeMeanChangeFromPriorYear`	number	Mean list price percent change — year-over-year delta
`listPricePercentChangeMeanFiveYearMonthlyMean`	number	Mean list price percent change — five-year monthly average
`listPricePercentChangeMedianChangeFromPriorMonth`	number	Median list price percent change — month-over-month delta
`listPricePercentChangeMedianChangeFromPriorYear`	number	Median list price percent change — year-over-year delta
`listPricePercentChangeMedianFiveYearMonthlyMedian`	number	Median list price percent change — five-year monthly median

`NewListings`

All fields are optional, nullable, and default to null.

Field	Type	Description
`inventoryCount`	`integer`	Number of new listings during the month
`listPriceMean`	`number`	Mean list price for new listings
`listPriceMedian`	`number`	Median list price for new listings
`listPriceStandardDeviation`	`number`	Standard deviation of list price for new listings

`PendingListings`

All fields are optional, nullable, and default to null.

Field	Type	Description
`inventoryCount`	`integer`	Number of listings that changed to pending during the month
`listPriceMean`	`number`	Mean list price for pending listings
`domMean`	`number`	Mean standard DOM before going pending
`cumulativeDomMean`	`number`	Mean cumulative DOM before going pending

`SoldListings`

All fields are optional, nullable, and default to null.

Field	Type	Description
`inventoryCount`	integer	Number of listings sold during the month
`inventoryCountChangeFromPriorMonth`	number	Sold count — month-over-month delta
`inventoryCountChangeFromPriorYear`	number	Sold count — year-over-year delta
`inventoryCountFiveYearMonthlyMean`	number	Sold count — five-year monthly average
`inventoryCountYearlyTotal`	number	Sold count — yearly total
`listPriceMean`	number	Mean list price for sold listings
`listPriceMeanChangeFromPriorMonth`	number	Mean sold list price — month-over-month delta
`listPriceMeanChangeFromPriorYear`	number	Mean sold list price — year-over-year delta
`listPriceMeanFiveYearMonthlyMean`	number	Mean sold list price — five-year monthly average
`listPricePerSquareFootMean`	number	Mean list price per square foot for sold listings
`listPricePerSquareFootMeanChangeFromPriorMonth`	number	Mean sold price/sqft — month-over-month delta
`listPricePerSquareFootMeanChangeFromPriorYear`	number	Mean sold price/sqft — year-over-year delta
`listPricePerSquareFootMeanFiveYearMonthlyMean`	number	Mean sold price/sqft — five-year monthly average
`domMean`	number	Mean standard DOM for sold listings
`domMeanChangeFromPriorMonth`	number	Mean sold DOM — month-over-month delta
`domMeanFiveYearMonthlyMean`	number	Mean sold DOM — five-year monthly average
`cumulativeDomMean`	number	Mean cumulative DOM for sold listings

`Delisted`

Listings removed from the market without selling (cancellations, expirations, withdrawals). All fields are optional, nullable, and default to null.

Field	Type	Description
`inventoryCount`	`integer`	Number of delisted listings during the month
`listPriceMean`	`number`	Mean list price for delisted listings
`domMean`	`number`	Mean standard DOM for delisted listings
`cumulativeDomMean`	`number`	Mean cumulative DOM for delisted listings

`MarketIndicator`

Buyer/seller market balance scores calculated as new listings ÷ 12-month moving average of sold listings. Values ≥ 1.5 indicate a buyer’s market, ≤ 1.0 indicate a seller’s market, and 1.0–1.5 indicate a balanced market. All fields are optional, nullable, and default to null.

Field	Type	Description
`buyerSellerMarketIndicatorMean`	`number`	Mean buyer/seller market indicator
`buyerSellerMarketIndicatorMedian`	`number`	Median buyer/seller market indicator
`buyerSellerMarketIndicatorStandardDeviation`	`number`	Standard deviation of the buyer/seller market indicator

Understanding DOM and comparison fields

Standard DOM: treats listings re-opened within 30 days as separate listings, tracking individual listing periods
Cumulative DOM: treats listings re-opened within 30 days as the same listing, tracking total time on market
Market Velocity: (active listings at month-end) ÷ (12-month moving average of sold listings)
Five-Year Monthly Mean/Median: historical baseline using five-year averages for comparison
Change-from-Prior: month-over-month, year-over-year, and five-year comparisons for trend analysis

Example response

{
  "success": true,
  "data": [
    {
      "analytics": [
        {
          "geographyType": "state",
          "geographyTypeValue": "CA",
          "trends": {
            "listingTrends": [
              {
                "state": "CA",
                "stateName": "California",
                "stateId": "06",
                "yearMonth": 202412,
                "dataPeriod": "457 - December 2024",
                "cbsaCode": null,
                "cbsaName": null,
                "countyFipsCode": null,
                "countyName": null,
                "zipCode": null,
                "marketVelocity": 1.2,
                "activeListings": {
                  "inventoryCount": 68423,
                  "inventoryCountChangeFromPriorMonth": -0.032,
                  "inventoryCountFiveYearMonthlyMean": 62100.4,
                  "listPriceMean": 1124000,
                  "listPriceMedian": 785000,
                  "listPriceStandardDeviation": 892000,
                  "domMean": 42,
                  "domMedian": 38,
                  "domStandardDeviation": 28.5,
                  "cumulativeDomMean": 48,
                  "cumulativeDomMedian": 41,
                  "cumulativeDomStandardDeviation": 32.1,
                  "monthsSupply": 2.8
                },
                "allListings": null,
                "closedListings": null,
                "newListings": {
                  "inventoryCount": 18200,
                  "listPriceMean": 895000,
                  "listPriceMedian": 725000,
                  "listPriceStandardDeviation": 654000
                },
                "pendingListings": {
                  "inventoryCount": 15830,
                  "listPriceMean": 810000,
                  "domMean": 22,
                  "cumulativeDomMean": 26
                },
                "soldListings": {
                  "inventoryCount": 24318,
                  "inventoryCountChangeFromPriorMonth": 0.045,
                  "inventoryCountChangeFromPriorYear": -0.012,
                  "inventoryCountFiveYearMonthlyMean": 23500.2,
                  "inventoryCountYearlyTotal": 289000,
                  "listPriceMean": 762000,
                  "listPriceMeanChangeFromPriorMonth": 0.008,
                  "listPriceMeanChangeFromPriorYear": 0.052,
                  "listPriceMeanFiveYearMonthlyMean": 710000,
                  "listPricePerSquareFootMean": 485,
                  "listPricePerSquareFootMeanChangeFromPriorMonth": 0.003,
                  "listPricePerSquareFootMeanChangeFromPriorYear": 0.048,
                  "listPricePerSquareFootMeanFiveYearMonthlyMean": 442,
                  "domMean": 31,
                  "domMeanChangeFromPriorMonth": -2,
                  "domMeanFiveYearMonthlyMean": 34,
                  "cumulativeDomMean": 36
                },
                "delisted": {
                  "inventoryCount": 8420,
                  "listPriceMean": 920000,
                  "domMean": 65,
                  "cumulativeDomMean": 72
                },
                "marketIndicator": {
                  "buyerSellerMarketIndicatorMean": 1.15,
                  "buyerSellerMarketIndicatorMedian": 1.10,
                  "buyerSellerMarketIndicatorStandardDeviation": 0.35
                }
              }
            ]
          }
        }
      ]
    }
  ],
  "count": 1,
  "messages": []
}

`pa-analytics_market_trends_tool`

Retrieve residential real estate market trends data for analyzing sales activity, equity positions, foreclosures, and market health. When to use:

You need home sales volumes, prices, or trends (total sales, resales, new construction)
Analyzing foreclosures, distressed properties, or REO/short sales
Evaluating equity positions, negative equity, or loan-to-value ratios
Assessing market conditions, housing stock, or delinquency rates

Examples:

“What are the total home sales in Los Angeles County this year?”
“Show me the foreclosure pipeline for Florida”
“Compare median sale prices across CBSAs 31080, 16980, and 35620”

Input schema

All analytics tools accept the shared AnalyticsFilter input.

Parameter	Type	Required	Description
`analytics_filter`	`AnalyticsFilter`	Yes	Geography and optional time range filter

Example request

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "pa-analytics_market_trends_tool",
    "arguments": {
      "analytics_filter": {
        "geography_filter": {
          "geography_type": "county_fips_code",
          "geography_type_values": ["06037"]
        },
        "time_range": {
          "from": { "year": 2024, "month": 1 },
          "to": { "year": 2024, "month": 12 }
        }
      }
    }
  }
}

Output schema

The analytics array contains elements with geographyType, geographyTypeValue, and a trends.marketTrends array. Each marketTrends record includes the shared geography fields plus the fields below.

Field	Type	Description
`loanCount`	`integer`	Total outstanding first-lien loans (~85% coverage)
`residentialHousingStock`	`integer`	Residential housing stock including SFA, SFD, townhouses, duplexes, triplexes, and condos (~85% coverage)
`totalSales`	`TotalSales`	Total sale counts and prices with change-from-prior comparisons
`resale`	`Resale`	Previously constructed home sales (excludes REO and short sales)
`newConstructionSales`	`NewConstructionSales`	Newly constructed residential unit sales
`reoSales`	`ReoSales`	Bank-owned property sales (~50% coverage)
`shortSales`	`ShortSales`	Sales where proceeds fall short of loan balance
`otherSales`	`OtherSales`	Non-arms-length transactions not covered by other categories
`equity`	`Equity`	Equity percentages, negative equity, and LTV ratios (quarterly updates from Sept 2009)
`foreclosure`	`Foreclosure`	Foreclosure pipeline: completed, active, 90+ day delinquent, and pre-foreclosure filings
`nonOwnerOccupied`	`NonOwnerOccupied`	Investment property percentages by origination type
`residentialMarketSales`	`ResidentialMarketSales`	Price-per-square-foot metrics with change-from-prior comparisons

`TotalSales`

Coverage is approximately 90%. All fields are optional, nullable, and default to null.

Field	Type	Description
`salesCount`	`integer`	Total home-sale transactions during the month
`salesCountChangeFromPriorMonth`	`number`	Sales count — month-over-month delta
`salesCountChangeFromPriorYear`	`number`	Sales count — year-over-year delta
`salesCountFiveYearMonthlyMean`	`number`	Sales count — five-year monthly average
`salesCountYearlyTotal`	`number`	Sales count — yearly total
`salesPriceMean`	`number`	Mean sale price for the month
`salesPriceMeanChangeFromPriorMonth`	`number`	Mean sale price — month-over-month delta
`salesPriceMeanChangeFromPriorYear`	`number`	Mean sale price — year-over-year delta
`salesPriceMeanFiveYearMonthlyMean`	`number`	Mean sale price — five-year monthly average
`salesPriceMedian`	`number`	Median sale price for the month

`Resale`

Previously constructed homes sold to unaffiliated third parties. Does not include REO or short sales. All fields are optional, nullable, and default to null.

Field	Type	Description
`salesCount`	`integer`	Number of resale transactions
`salesPriceMean`	`number`	Mean resale price
`salesPriceMedian`	`number`	Median resale price

`NewConstructionSales`

All fields are optional, nullable, and default to null.

Field	Type	Description
`salesCount`	`integer`	Number of new-construction sales
`salesPriceMean`	`number`	Mean new-construction sale price
`salesPriceMedian`	`number`	Median new-construction sale price

`ReoSales`

Bank-owned properties sold to an unaffiliated third party. Coverage is approximately 50%. All fields are optional, nullable, and default to null.

Field	Type	Description
`loanCount`	`integer`	Number of REO loans
`salesCount`	`integer`	Number of REO properties sold
`salesPriceMean`	`number`	Mean REO sale price
`salesPriceMedian`	`number`	Median REO sale price

`ShortSales`

Sales where proceeds fall short of the balance owed on the property’s loan. All fields are optional, nullable, and default to null.

Field	Type	Description
`salesCount`	`integer`	Number of short sales
`salesPriceMean`	`number`	Mean short-sale price
`salesPriceMedian`	`number`	Median short-sale price

`OtherSales`

Non-arms-length transactions not accounted for by resales, REO, or short sales. All fields are optional, nullable, and default to null.

Field	Type	Description
`salesCount`	`integer`	Number of other sales
`salesPriceMean`	`number`	Mean other-sale price
`salesPriceMedian`	`number`	Median other-sale price

`Equity`

Updated quarterly from September 2009. Monthly values between quarterly updates are interpolated by dividing the quarterly difference by three. All fields are optional, nullable, and default to null.

Field	Type	Description
`equityPercentage`	`number`	Equity percentage — calculated as `1 − LTV`
`negativeEquityLoans`	`integer`	Number of mortgaged properties in negative equity
`negativeEquityShare`	`number`	Share of mortgaged properties in negative equity (decimal fraction)
`totalLtvMedian`	`number`	Median loan-to-value ratio

`Foreclosure`

Coverage is approximately 85% for foreclosures and 75–90% for 90+ day delinquency (varies by market). These are directional indicators, not complete tallies. All fields are optional, nullable, and default to null.

Field	Type	Description
`completedForeclosures`	`integer`	Properties sold at public auction due to missed payments
`foreclosures`	`integer`	Loans currently in the foreclosure process
`ninetyDayPlusDelinquency`	`integer`	Mortgages delinquent 90+ days (includes REO/foreclosure, prime and subprime)
`preForeclosureFilings`	`integer`	Mortgages with foreclosure proceedings initiated via public notice (NOD)

`NonOwnerOccupied`

Percentages based on origination month. All fields are optional, nullable, and default to null.

Field	Type	Description
`percentPurchases`	`number`	Percent of purchase originations attributed to non-owner occupied properties
`percentRefinances`	`number`	Percent of refinance originations attributed to non-owner occupied
`percentTotal`	`number`	Percent of total originations attributed to non-owner occupied

`ResidentialMarketSales`

All fields are optional, nullable, and default to null.

Field	Type	Description
`salesPricePerSquareFootMean`	`number`	Mean sale price per square foot
`salesPricePerSquareFootMeanChangeFromPriorMonth`	`number`	Mean price/sqft — month-over-month delta
`salesPricePerSquareFootMeanChangeFromPriorYear`	`number`	Mean price/sqft — year-over-year delta
`salesPricePerSquareFootMeanFiveYearMonthlyMean`	`number`	Mean price/sqft — five-year monthly average
`salesPriceYearlyTotal`	`number`	Total sales price for the year

`pa-analytics_rental_trends_tool`

Retrieve rental market trends data for analyzing rental prices, inventory, vacancy rates, and capitalization rates in the residential rental sector. When to use:

You need rental prices, rent levels, or rental rate data (mean, median, min, max)
Evaluating vacancy rates or rental availability
Reviewing capitalization rates (cap rates) for rental properties
Comparing rental trends by property type or bedroom count

Examples:

“What is the median rent for a 3-bedroom single-family home in CBSA 31080?”
“Show me vacancy rates for ZIP code 98101”
“Compare cap rates across New York state by property type”

Input schema

All analytics tools accept the shared AnalyticsFilter input.

Parameter	Type	Required	Description
`analytics_filter`	`AnalyticsFilter`	Yes	Geography and optional time range filter

Example request

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "pa-analytics_rental_trends_tool",
    "arguments": {
      "analytics_filter": {
        "geography_filter": {
          "geography_type": "cbsa_code",
          "geography_type_values": ["31080"]
        }
      }
    }
  }
}

Output schema

The analytics array contains elements with geographyType, geographyTypeValue, and a trends.rentalTrends array. Each rentalTrends record includes the shared geography fields plus the field below.

Field	Type	Description
`rentalTrendsDetails`	`array[RentalTrendsDetails]`	Rental metrics broken down by property type and bedroom count

`RentalTrendsDetails`

Each element represents a specific combination of property type and bedroom count.

Field	Type	Description
`propertyType`	`string`	Property type description (e.g., `"Single Family - Detached"`)
`bedroomCount`	`integer`	Number of bedrooms
`rentMean`	`integer`	Mean rent for the period
`rentMedian`	`integer`	Median rent for the period
`rentMin`	`integer`	5th percentile of rent amounts
`rentMax`	`integer`	95th percentile of rent amounts
`rentSquareFootageMean`	`number`	Mean rent per square foot
`rentSquareFootageMedian`	`number`	Median rent per square foot
`vacancyRate`	`number`	Estimated percentage of available units that are vacant (decimal fraction)
`capitalizationRateMean`	`number`	Mean cap rate — Net Operating Income ÷ Asset Acquisition Cost
`capitalizationRateMedian`	`number`	Median cap rate — Net Operating Income ÷ Asset Acquisition Cost

Property types include:

Single Family Detached (1–4 bedrooms)
Single Family Attached (1–3 bedrooms)
Single Family Combined (1–4 bedrooms)

Cap rate formula: Net Operating Income = Total Rental Income − Total Operating Cost Operating costs include property tax, property management fees, maintenance, lease/damages, liability insurance, and vacancy loss.

Example response

{
  "success": true,
  "data": [
    {
      "analytics": [
        {
          "geographyType": "cbsa_code",
          "geographyTypeValue": "31080",
          "trends": {
            "rentalTrends": [
              {
                "state": "CA",
                "stateName": "California",
                "stateId": "06",
                "cbsaCode": "31080",
                "cbsaName": "Los Angeles-Long Beach-Anaheim, CA",
                "countyFipsCode": null,
                "countyName": null,
                "yearMonth": 202412,
                "dataPeriod": "457 - December 2024",
                "zipCode": null,
                "rentalTrendsDetails": [
                  {
                    "propertyType": "Single Family - Detached",
                    "bedroomCount": 3,
                    "rentMean": 3480,
                    "rentMedian": 3200,
                    "rentMin": 2100,
                    "rentMax": 5800,
                    "rentSquareFootageMean": 2.18,
                    "rentSquareFootageMedian": 1.95,
                    "vacancyRate": 0.047,
                    "capitalizationRateMean": 0.044,
                    "capitalizationRateMedian": 0.042
                  },
                  {
                    "propertyType": "Single Family - Detached",
                    "bedroomCount": 4,
                    "rentMean": 4250,
                    "rentMedian": 3950,
                    "rentMin": 2700,
                    "rentMax": 7200,
                    "rentSquareFootageMean": 1.92,
                    "rentSquareFootageMedian": 1.78,
                    "vacancyRate": 0.038,
                    "capitalizationRateMean": 0.041,
                    "capitalizationRateMedian": 0.039
                  }
                ]
              }
            ]
          }
        }
      ]
    }
  ],
  "count": 1,
  "messages": []
}

`pa-analytics_corelogic_hpi_tool`

Retrieve Cotality Home Price Index (HPI) data measuring changes in housing market prices from 1976 through the present. The HPI uses a repeat-sales, value-weighted econometric model with base year 2000 = 100. In geographies with insufficient data, the index is infilled using state-level monthly growth rates. When to use:

You need current or historical home price index values
Tracking home price appreciation or depreciation over time
Analyzing market volatility, price stability, or standard deviation of prices
Evaluating whether markets are overvalued or undervalued

Examples:

“What is the current HPI for California?”
“Show me HPI trends for county 06037 from 2020 to 2025”
“Is CBSA 31080 currently overvalued or undervalued?”

Input schema

All analytics tools accept the shared AnalyticsFilter input.

Parameter	Type	Required	Description
`analytics_filter`	`AnalyticsFilter`	Yes	Geography and optional time range filter

Example request

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "pa-analytics_corelogic_hpi_tool",
    "arguments": {
      "analytics_filter": {
        "geography_filter": {
          "geography_type": "state",
          "geography_type_values": ["CA"]
        },
        "time_range": {
          "from": { "year": 2024, "month": 1 },
          "to": { "year": 2024, "month": 12 }
        }
      }
    }
  }
}

Output schema

The analytics array contains elements with geographyType, geographyTypeValue, and an indices.corelogicHpi array. Each corelogicHpi record includes the shared geography fields plus the fields below.

Field	Type	Description
`lastUpdateDate`	`string`	Last date the index series was updated for this geography (stale series may resume if sufficient transactions become available)
`hpiTier`	`array[HpiTier]`	Index values and statistics broken down by tier (price segment)

`HpiTier`

Field	Type	Description
`tierCode`	`integer`	Tier code (0–9, 11, or 12) standardized by Cotality
`tierName`	`string`	Description for the tier
`homePriceIndex`	`number`	HPI value (base year 2000 = 100)
`repeatSalesCount`	`integer`	Number of repeat sales used to build the index for this period
`repeatSalesMedian`	`number`	Median home price for repeat-sales observations
`standardDeviation`	`number`	Standard error of model coefficients (observed values around the estimated regression line)
`volatilityIndex`	`number`	12-month moving average of standard deviation
`longTermFundamentalValue`	`number`	Long-term fundamental HPI derived from real disposable income per capita (top CBSAs only)
`marketIndicator`	`string`	Market condition: `"OVERVALUED"` (>10% above fundamental), `"UNDERVALUED"` (>10% below), or `"NORMAL"` (top CBSAs only)
`startDate`	`string`	Date the index series was first created for this geography
`endDate`	`string`	Most recent date the index series was updated using native geography data (not infilled)
`disNondisFlag`	`integer`	Non-disclosure flag — 1 indicates a non-disclosure state/county where transaction sale prices are not publicly available

`pa-analytics_corelogic_hpi_forecast_tool`

Retrieve Cotality Home Price Index (HPI) forecast data providing predicted future index values for market analysis and planning. The forecast model uses a two-stage error correction methodology combining equilibrium housing price with short-run price fluctuations affected by market momentum, mean reversion, and exogenous economic shocks. When to use:

You need predicted future home price index values
Evaluating expected home price appreciation or depreciation
Assessing forecast uncertainty or prediction confidence
Planning around long-term price expectations or market projections

Examples:

“What is the HPI forecast for CBSA 31080 over the next 12 months?”
“Show me the predicted market condition for California through 2026”
“What is the forecast confidence interval for Chicago’s HPI?”

Input schema

All analytics tools accept the shared AnalyticsFilter input.

Parameter	Type	Required	Description
`analytics_filter`	`AnalyticsFilter`	Yes	Geography and optional time range filter

Example request

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "pa-analytics_corelogic_hpi_forecast_tool",
    "arguments": {
      "analytics_filter": {
        "geography_filter": {
          "geography_type": "cbsa_code",
          "geography_type_values": ["31080"]
        },
        "time_range": {
          "from": { "year": 2025, "month": 1 },
          "to": { "year": 2026, "month": 12 }
        }
      }
    }
  }
}

Output schema

The analytics array contains elements with geographyType, geographyTypeValue, and an indices.corelogicHpiForecast array. Each corelogicHpiForecast record includes the shared geography fields plus the field below.

Field	Type	Description
`hpiForecastTier`	`array[HpiForecastTier]`	Forecast values and statistics broken down by tier

`HpiForecastTier`

Field	Type	Description
`tierCode`	`integer`	Tier code (0–9, 11, or 12) standardized by Cotality
`tierName`	`string`	Description for the tier
`hpiForecast`	`number`	Forecasted HPI value (base year 2000 = 100)
`hpiForecastStandardError`	`number`	Standard error used to calculate the 95% confidence interval — `SE = (UL − LL) / (2 × 1.96)`
`longTermFundamentalValue`	`number`	Long-term fundamental HPI derived from real disposable income per capita (top CBSAs only)
`marketIndicator`	`string`	Forecasted market condition: “OVERVALUED” (>10% above fundamental), “UNDERVALUED” (>10% below), or “NORMAL” (top CBSAs only)

Example response

{
  "success": true,
  "data": [
    {
      "analytics": [
        {
          "geographyType": "cbsa_code",
          "geographyTypeValue": "31080",
          "indices": {
            "corelogicHpiForecast": [
              {
                "state": "CA",
                "cbsaCode": "31080",
                "cbsaName": "Los Angeles-Long Beach-Anaheim, CA",
                "yearMonth": 202506,
                "dataPeriod": "463 - June 2025",
                "hpiForecastTier": [
                  {
                    "tierCode": 0,
                    "tierName": "All Tiers",
                    "hpiForecast": 428.7,
                    "hpiForecastStandardError": 18.4,
                    "longTermFundamentalValue": 389.2,
                    "marketIndicator": "OVERVALUED"
                  }
                ]
              }
            ]
          }
        }
      ]
    }
  ],
  "count": 1,
  "messages": []
}

​Shared input: AnalyticsFilter

​AnalyticsFilter

​AnalyticsGeographyFilter

​Geography types

​TimeRange

​YearMonth

​Example filter

​Response envelope

​Shared geography response fields

​Reading numeric values

​pa-analytics_listing_trends_tool

​Input schema

​Example request

​Output schema

​ActiveListings

​AllListings

​ClosedListings

​NewListings

​PendingListings

​SoldListings

​Delisted

​MarketIndicator

​Understanding DOM and comparison fields

​Example response

​pa-analytics_market_trends_tool

​Input schema

​Example request

​Output schema

​TotalSales

​Resale

​NewConstructionSales

​ReoSales

​ShortSales

​OtherSales

​Equity

​Foreclosure

​NonOwnerOccupied

​ResidentialMarketSales

​pa-analytics_rental_trends_tool

​Input schema

​Example request

​Output schema

​RentalTrendsDetails

​Example response

​pa-analytics_corelogic_hpi_tool

​Input schema

​Example request

​Output schema

​HpiTier

​pa-analytics_corelogic_hpi_forecast_tool

​Input schema

​Example request

​Output schema

​HpiForecastTier

​Example response

Shared input: `AnalyticsFilter`

`AnalyticsFilter`

`AnalyticsGeographyFilter`

Geography types

`TimeRange`

`YearMonth`

Example filter

Response envelope

Shared geography response fields

Reading numeric values

`pa-analytics_listing_trends_tool`

Input schema

Example request

Output schema

`ActiveListings`

`AllListings`

`ClosedListings`

`NewListings`

`PendingListings`

`SoldListings`

`Delisted`

`MarketIndicator`

Understanding DOM and comparison fields

Example response

`pa-analytics_market_trends_tool`

Input schema

Example request

Output schema

`TotalSales`

`Resale`

`NewConstructionSales`

`ReoSales`

`ShortSales`

`OtherSales`

`Equity`

`Foreclosure`

`NonOwnerOccupied`

`ResidentialMarketSales`

`pa-analytics_rental_trends_tool`

Input schema

Example request

Output schema

`RentalTrendsDetails`

Example response

`pa-analytics_corelogic_hpi_tool`

Input schema

Example request

Output schema

`HpiTier`

`pa-analytics_corelogic_hpi_forecast_tool`

Input schema

Example request

Output schema

`HpiForecastTier`

Example response