Skip to main content
GET
/
api
/
v1
/
search
/
for-rent
Search Properties For Rent
curl --request GET \
  --url https://us-red-property-data.p.rapidapi.com/api/v1/search/for-rent \
  --header 'x-rapidapi-key: <api-key>'
{
  "success": true,
  "cost": 1,
  "total": 792,
  "has_more": true,
  "data": [
    {
      "property_id": "9525905454",
      "listing_id": "2966802712",
      "list_price": null,
      "list_price_max": 2353,
      "list_price_min": 1325,
      "permalink": "1676-Maryland-Ave-NE_Washington_DC_20002_M95259-05454",
      "price_reduced_amount": null,
      "matterport": false,
      "has_specials": true,
      "application_url": null,
      "status": "for_rent",
      "list_date": "2024-04-26T18:46:28.000000Z",
      "available_date_change_timestamp": "2026-02-15T01:17:05.394",
      "branding": [
        {
          "type": "Office",
          "photo": null,
          "name": null
        }
      ],
      "source": {
        "id": "ZILL",
        "community_id": 4352806,
        "type": "community",
        "feed_type": "Syndicator Community"
      },
      "details": [
        {
          "category": "Community Features",
          "text": [
            "Barbecue Area",
            "Bicycle storage",
            "Cable/Internet Ready"
          ]
        }
      ],
      "products": {
        "products": [
          "co_broke",
          "rentals_cost_per_lead_hybrid"
        ],
        "brand_name": "basic_opt_in"
      },
      "rentals_application_eligibility": {
        "estimated_status": "BLOCKED"
      },
      "flags": {
        "is_pending": null,
        "is_new_listing": false,
        "has_new_availability": true
      },
      "photos": [
        {
          "href": "https://ar.rdcpix.com/270ee3cad0607d29b04dc1d9c221146cc-f2193502019s.jpg"
        }
      ],
      "primary_photo": {
        "href": "https://ar.rdcpix.com/270ee3cad0607d29b04dc1d9c221146cc-f2193502019s.jpg"
      },
      "search_promotions": null,
      "virtual_tours": null,
      "lead_attributes": {
        "lead_type": "rental_go_direct",
        "is_premium_ldp": false,
        "is_schedule_a_tour": false
      },
      "pet_policy": {
        "cats": true,
        "dogs": true,
        "dogs_small": false,
        "dogs_large": false
      },
      "description": {
        "beds": null,
        "beds_max": 2,
        "beds_min": 0,
        "baths_min": 1,
        "baths_max": 2,
        "baths_consolidated": null,
        "baths": null,
        "sqft": null,
        "sqft_max": 1091,
        "sqft_min": 459,
        "name": "Union Heights",
        "sub_type": null,
        "type": "apartment"
      },
      "other_listings": {
        "rdc": [
          {
            "listing_id": "2966802712",
            "status": "for_rent"
          }
        ]
      },
      "advertisers": [
        {
          "type": "management",
          "office": {
            "name": "Greystar"
          },
          "rental_management": null
        }
      ],
      "location": {
        "address": {
          "coordinate": {
            "lat": 38.901192,
            "lon": -76.975883
          },
          "line": "1676 Maryland Ave NE",
          "city": "Washington",
          "country": "USA",
          "state_code": "DC",
          "postal_code": "20002"
        },
        "county": {
          "name": "District of Columbia"
        }
      },
      "units": [
        {
          "availability": {
            "date": "2026-02-18"
          },
          "description": {
            "baths_consolidated": null,
            "baths": 2,
            "beds": 2,
            "sqft": 985
          },
          "list_price": 2054
        }
      ]
    }
  ]
}

Authorizations

​
x-rapidapi-key
string
header
required

Rapid API Key

Query Parameters

​
location
string
required

Location

Minimum string length: 1
Example:

"20002"

​
page
integer
default:1

Page number for pagination

Example:

1

​
sort_by
enum<string>
default:best_match

Sort results by the specified criteria

  • best_match: Best match
  • recently_added: Recently added
  • highest_price: Highest price
  • lowest_price: Lowest price
Available options:
best_match,
recently_added,
highest_price,
lowest_price
Example:

"best_match"

​
list_price_range
string

list_price_range filter in format min,max

Example 50000,1000000 means price from $50,000 to $1,000,000

Example:

"50000,1000000"

​
property_type
string

Filter listings by property type

You can use one or multiple values separated by commas ,

  • apartment: Apartment
  • townhome: Townhome
  • condo: Condo
  • single_family: Single family
Example:

"apartment,townhome"

​
number_of_bedrooms
integer

Filter by minimum number of bedrooms. The value represents the lower bound. For example, if 1 is provided, the query will return properties with 1 or more bedrooms (bedrooms >= 1)

Example:

1

​
number_of_bathrooms
integer

Filter by minimum number of bathrooms. The value represents the lower bound. For example, if 1 is provided, the query will return properties with 1 or more bathrooms (bathrooms >= 1)

Example:

1

​
move_in_by
string

Desired move-in date. Format YYYY-MM-DD (ISO 8601)

Pattern: ^\d{4}-(0[1-9]|1[0-2])-(0[1-9]|[12]\d|3[01])$
Example:

"2026-01-31"

​
pet_friendly
string

Filter listings by pet friendly

You can use one or multiple values separated by commas ,

  • cats: Cats OK
  • dogs: Dogs OK
Example:

"cats,dogs"

​
square_feet_range
string

square_feet_range filter in format min,max

Example 500,2000 square feet from 500 to 2000

Example:

"500,2000"

​
is_accepts_online_applications
boolean

Accepts online applications

Example:

true

​
is_3d_tours
boolean

3D Tours

Example:

true

​
unit_features
string

Filter listings by unit features

You can use one or multiple values separated by commas ,

  • washer_dryer: Washer / dryer
  • central_air: Central air
Example:

"washer_dryer,central_air"

​
community_features
string

Filter listings by community features

You can use one or multiple values separated by commas ,

  • garage_1_or_more: Parking
  • community_gym: Gym
  • community_swimming_pool: Pool(s)
  • laundry_room: Laundry room
Example:

"garage_1_or_more,community_gym"

​
keyword_search
string

Filter listings by keyword search

You can use one or multiple values separated by commas ,

Example:

"Pool,Lake view"

Response

Success

​
success
boolean
Example:

true

​
cost
number

Cost of the request

Example:

1

​
total
number

Total number of properties matching the search criteria

Example:

792

​
has_more
boolean

Whether there are more data to fetch

Example:

true

​
data
object[]