Base properties (baseProperties)

The Insights Base Property query (baseProperties) returns U.S. assessor and public-record style property rows from the BaseProperties OData entity. Each row is keyed by CID together with county FIPS and parcel context. The GraphQL schema groups attributes into objects such as location, characteristics, structure, tax, latestTransfer, currentLoans, and estimatedValue, plus optional history expansions: historicalEstimate, taxHistory, salesAndTransferHistory, and mortgageHistory.

Connection result

Endpoint

POST /graphql

Root query (example)

query BasePropertyQuery(
  $filter: BasePropertyFilter!
  $limit: Int
  $offset: Int
  $orderBy: BasePropertySort
) {
  baseProperties(filter: $filter, limit: $limit, offset: $offset, orderBy: $orderBy) {
    totalCount
    nodes {
      cid
      countyFipsCode
      parcelNumber
      modificationTimestamp
      propertyType
      propertySubType
      location {
        address { unparsedAddress city stateOrProvince postalCode }
        census {
          administrative {
            countyOrParish {
              id
              name
              stateOrProvince
              country
              type
              geom
              latitude
              longitude
              version
            }
          }
        }
        gis { latitude longitude }
      }
      characteristics { lotSizeSquareFeet view poolFeatures }
      structure {
        bedroomsTotal
        bathroomsTotalInteger
        livingArea
        yearBuilt
      }
      latestTransfer { salesPrice recordingDate }
      estimatedValue { estimate confidenceScore }
      historicalEstimate(limit: 4) {
        estimateDate
        estimate
        rangeMin
        rangeMax
      }
      taxHistory {
        taxYear
        taxAnnualAmount
        taxAssessedValue
        marketValue
      }
      salesAndTransferHistory(limit: 5, orderBy: { modificationTimestamp: DESC }) {
        transactionId
        recordingDate
        salesPrice
        sellerFullName1
        buyerFullName1
        titleCompanyName
      }
      mortgageHistory(limit: 5, orderBy: { modificationTimestamp: DESC }) {
        loanId
        transactionId
        loanAmount
        interestRate
        loanType
        lenderNameBeneficiary
        recordingDate
      }
      resoProperties { listingKey }
    }
  }
}

Variables (example)

{
  "filter": {
    "countyFipsCode": { "eq": "06037" },
    "polygon": {
      "wkt": "POLYGON((-118.5 34.0, -118.3 34.0, -118.3 34.2, -118.5 34.2, -118.5 34.0))"
    },
    "structure": { "bedroomsTotal": { "ge": 3 }, "livingArea": { "ge": 1500 } },
    "estimatedValue": { "estimate": { "lt": 1000000 } },
    "dates": { "modificationTimeStamp": { "ge": "2026-01-01" } }
  },
  "limit": 10,
  "offset": 0,
  "orderBy": {
    "latestTransfer": { "recordingDate": "DESC" },
    "estimatedValue": { "estimate": "ASC" }
  }
}

How filtering works

Arguments use the input type BasePropertyFilter. The server forwards filters to Insights as an OData $filter string.

• Flat vs nested: You may pass a single “flat” object of conditions (e.g. countyFipsCode + structure). The resolver wraps it as { and: filter } when you do not supply top-level and or or, so all clauses are combined with AND.
• Explicit logic: To use OR or mixed logic, structure variables with top-level and or or keys whose values are objects of field filters (same pattern as other Insights-backed queries).
• Nested sections: Filters mirror the schema: e.g. location.address.city, structure.livingArea, latestTransfer.salesPrice, estimatedValue.estimate, dates.modificationTimeStamp.
• Polygon search: Use top-level polygon with wkt (a WKT POLYGON string of longitude/latitude pairs). The server maps this to OData geo.intersects(location, geography'POLYGON((...))'). The ring must be closed (first and last coordinate pair identical).
• Operators: StringFilter supports eq, contains, startswith; IntFilter and FloatFilter support eq, gt, ge, lt, le; DateTimeFilter supports eq, gt, ge, lt, le (ISO date strings).
• Enums: propertyType and propertySubType use GraphQL enums (e.g. Residential, SingleFamilyResidence) - pass them without wrapping in eq at the filter field.
• OData mapping: GraphQL cid maps to OData CID; dates.modificationTimeStamp maps to OData modificationTimestamp.

How sorting works

Use optional orderBy: BasePropertySort. Only certain leaf fields are mapped to OData $orderby:

Each sort direction is ASC or DESC (SortOrder enum). Multiple groups can appear in one orderBy object; the server builds a comma-separated OData order list.

How expansion works

In GraphQL, “expansion” means requesting nested fields in the query. There are no separate REST-style expand parameters.

• Nested objects: Ask for location { address census gis }, tax { … }, occupantOwner { … }, etc. Null objects appear when the source has no data.
• location.gis.parcel: Resolved via DataLoader / ParcelBoundary API by CID (extra round-trip when selected).
• History fields: Request historicalEstimate, taxHistory, salesAndTransferHistory, or mortgageHistory under each BaseProperty node. Each loads a related Insights history entity by CID (batched). Omit them to avoid the extra work. If Insights denies a history entity (HTTP 403), that field resolves to null and GraphQL may include an entry in errors while the rest of baseProperties still returns.
• resoProperties: When listed under BaseProperty, the resolver loads linked MLS/RESO listings for the same CID (batched per request). Omit this field to avoid that work.

Pagination

Operators (filter leaf inputs)

BaseProperty - root fields (schema)

Nested highlights: location.address (full addressing components); location.census (administrative, legislative, statistical GeoIDs and boundary details); location.gis (lat/long, precision, parcel boundary); latestTransfer.buyers/sellers arrays; currentLoans.loans array of BaseLoan.

Historical fields (schema detail)

History fields are requested on each BaseProperty node. They are not part of the root BasePropertyFilter; filtering and sorting for history apply only to that field’s arguments. If the caller’s Insights credentials lack access to a history entity, that field returns null (with a GraphQL error) and the rest of the base property payload is unchanged.

historicalEstimate → [BaseHistoricalEstimate!]

Backed by OData AvmHistoryAggregate. Returns monthly AVM point estimates for the property.

taxHistory → [BaseTaxHistory!]

Backed by OData AssessorHistoryAggregate. Returns annual tax and assessment history.

See GraphQL introspection for the full BaseTaxHistory leaf list (exemptions, certification date, value-per-sqft fields, and related flags).

salesAndTransferHistory → [BaseSalesAndTransferHistory!]

Backed by OData SalesAndTransferHistory. Returns recorded sales and ownership transfers for the property.

mortgageHistory → [BaseMortgageHistory!]

Backed by OData MortgageHistoryAggregate. Returns historical mortgage and lien records for the property.

See GraphQL introspection for the complete BaseMortgageHistory and BaseSalesAndTransferHistory field lists.

Example history selection

nodes {
  cid
  estimatedValue { estimate confidenceScore }
  historicalEstimate(limit: 12, orderBy: { estimateDate: DESC }) {
    estimateDate
    estimate
    rangeMin
    rangeMax
  }
  taxHistory(filter: { taxYear: { ge: 2018 } }, orderBy: { taxYear: DESC }) {
    taxYear
    taxAnnualAmount
    taxAssessedValue
    marketValue
  }
  salesAndTransferHistory(limit: 10, orderBy: { modificationTimestamp: DESC }) {
    transactionId
    recordingDate
    salesPrice
    buyerFullName1
    sellerFullName1
  }
  mortgageHistory(limit: 10, orderBy: { modificationTimestamp: DESC }) {
    loanId
    loanAmount
    interestRate
    lenderNameBeneficiary
    recordingDate
  }
}

CensusGeo fields (used under location.census.*)

Example response (abbreviated)

{
  "data": {
    "baseProperties": {
      "totalCount": 1,
      "nodes": [{
        "cid": "06037123456",
        "countyFipsCode": "06037",
        "parcelNumber": "1234-567-890",
        "modificationTimestamp": "2026-01-10",
        "propertyType": "Residential",
        "structure": { "bedroomsTotal": 4, "livingArea": 2500 },
        "estimatedValue": { "estimate": 1012000, "confidenceScore": 95 }
      }]
    }
  }
}