FurnishedFinder Rental Scraper

Hunting for furnished housing on FurnishedFinder usually means opening dozens of listings, jotting down the rent, counting bedrooms, and checking what's actually available. This scraper does the legwork. Give it a city or a postal code and every rental comes back as a tidy row — monthly rent, bedrooms, bathrooms, amenities, and availability already split into fields and ready for a spreadsheet or a model. It runs fast, costs little, needs no code, and you pay only for what you scrape.

What you get

Each rental comes back as one row, grouped into three kinds of data:

• The place — rentalId, rentalUrl, photoUrl, headline, rentalType, cityState
• Rent and rooms — monthlyRent, bedroomCount, bathroomCount, availableNow, amenityTags
• Run context — resultRank, searchedFor, collectedAt

Quick start

1. Hit Try for free and type your target cities into Search areas (for example Denver, CO), or drop US codes into Postal codes.
2. Set Earliest move-in and Latest move-out if you have a stay window in mind, and add a Lowest or Highest monthly rent to trim the budget.
3. Use Listings per area to cap how many rentals come back from each city or code.
4. Press Start, then export the rows as JSON, CSV, Excel, or XML.

Use cases

• Relocation planning — line up furnished options in a new city before you ever fly out
• Travel nurse and contractor housing — match rentals to an assignment window with the move-in and move-out filters
• Rent benchmarking — see what furnished places actually charge per month across neighborhoods
• Property manager research — track competing listings, amenities, and availability in your market
• Corporate housing teams — pull a clean shortlist of options to send clients

Input

Field	Type	Required	Description
searchAreas	array of strings	One of searchAreas or postalCodes	Cities to search, one per line. Accepts City, State, City, State Zip, or a full street address. Prefilled with Denver, CO.
postalCodes	array of strings	One of searchAreas or postalCodes	US postal codes to search, one per line; city and state are resolved for you.
startDate	string	No	Earliest move-in date as YYYY-MM-DD, applied to every area. Leave blank to skip date filtering.
endDate	string	No	Latest move-out date as YYYY-MM-DD. Pair with the move-in date to target a stay window.
minRent	integer	No	Drop listings below this monthly rent in USD.
maxRent	integer	No	Drop listings above this monthly rent in USD.
resultsLimit	integer	No	How many listings to gather per area. Default 25.
timeoutSeconds	integer	No	Seconds to wait on each request before giving up. Default 45.

Example input

{
    "searchAreas": ["Denver, CO"],
    "postalCodes": ["80202"],
    "startDate": "2026-08-01",
    "endDate": "2026-12-01",
    "minRent": 1200,
    "maxRent": 4500,
    "resultsLimit": 25,
    "timeoutSeconds": 45
}

Output

Every rental on the search results becomes one row, with pagination handled for you up to the limit you set. Fields that a listing card doesn't show come back empty rather than guessed.

Example output

{
    "rentalId": "994889_1",
    "rentalUrl": "https://www.furnishedfinder.com/property/994889_1",
    "photoUrl": "https://media.furnishedfinder.com/property/994889/main.jpg",
    "headline": "Bright furnished 2-bed near downtown Denver",
    "rentalType": "Apartment",
    "cityState": "Denver, CO",
    "monthlyRent": 2400,
    "bedroomCount": 2,
    "bathroomCount": 1,
    "availableNow": true,
    "amenityTags": ["WiFi", "Utilities Included", "Parking"],
    "resultRank": 1,
    "searchedFor": "Denver, CO",
    "collectedAt": "2026-06-29T12:00:00.000000+00:00"
}

Output fields

Field	Type	Description
rentalId	string	FurnishedFinder identifier for the rental, e.g. 994889_1
rentalUrl	string	Direct link to the rental's detail page
photoUrl	string	Link to the main photo on the listing card
headline	string	Listing headline as shown in search results
rentalType	string	House, Apartment, Room, Condo, or Studio
cityState	string	City and state of the rental, e.g. Brooklyn, NY
monthlyRent	integer	Rent per month in USD; empty when not readable
bedroomCount	integer	Number of bedrooms; empty when not listed
bathroomCount	integer	Number of bathrooms; empty when not listed
availableNow	boolean	True when the card reads Available, false when Unavailable
amenityTags	array	Amenity labels from the card, e.g. WiFi, Utilities Included
resultRank	integer	Position in the search results, counting from 1
searchedFor	string	The city or postal code you entered that surfaced this rental
collectedAt	string	ISO 8601 UTC timestamp of when the row was captured

Tips for best results

• Mix cities and codes freely. Put cities in searchAreas and codes in postalCodes; each entry runs on its own up to your per-area cap.
• Start small. Run resultsLimit at 25 to confirm the output fits your pipeline, then raise it for the full pull.
• Set a realistic budget. Most furnished rentals run $1,000+/mo, so a very low maxRent can return nothing — widen it or drop the filter if results dry up.
• Use the date window for assignments. startDate and endDate together narrow results to rentals open during your stay.
• Raise timeoutSeconds if you hit timeouts on big multi-city runs.

How can I use FurnishedFinder rental data?

How can I use the FurnishedFinder Rental Scraper to compare furnished rent across cities? List several cities in searchAreas, set a resultsLimit, and run it. Each row carries monthlyRent, bedroomCount, cityState, and searchedFor, so you can group by city and read the going rate for furnished housing side by side.

How can I find furnished housing for a travel assignment with a set move-in and move-out? Enter your destination as a city or postal code, then fill in startDate and endDate to match your contract dates. The scraper returns only rentals open in that window, with availableNow and amenityTags so you can shortlist fast.

How can I build a FurnishedFinder dataset for rent research or a market dashboard? Feed in your target areas, cap the volume with resultsLimit, and export to CSV or Excel. You get a structured rental database — rent, beds, baths, amenities, availability, and location — that you can chart, filter, or pipe into your own tool.

Is it legal to scrape data?

Our actors are ethical and do not extract any private user data, such as email addresses or private contact information. They only extract what the user has chosen to share publicly. We therefore believe that our actors, when used for ethical purposes by Apify users, are safe.

However, you should be aware that your results could contain personal data. Personal data is protected by the GDPR in the European Union and by other regulations around the world. You should not scrape personal data unless you have a legitimate reason to do so. If you're unsure whether your reason is legitimate, consult your lawyers.

You can also read Apify's blog post on the legality of web scraping.

Support

Questions, feature requests, or a field you'd like added? Reach out at data.apify@proton.me and we'll get back to you.