# FurnishedFinder Scraper (Cheap) (`data_api/furnishedfinder-scraper-cheap`) Actor FurnishedFinder rental extractor that pulls listings by city and move-in date, so you get price, availability, bedrooms, and amenities in one automated run. - **URL**: https://apify.com/data\_api/furnishedfinder-scraper-cheap.md - **Developed by:** [Data API](https://apify.com/data_api) (community) - **Categories:** Automation, Real estate, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.99 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## FurnishedFinder Rental Scraper ![FurnishedFinder Rental Scraper](cover.jpg) 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. ![How it works](how-it-works.jpg) ### 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 ```json { "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 ```json { "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](https://blog.apify.com/is-web-scraping-legal/). ### Support Questions, feature requests, or a field you'd like added? Reach out at and we'll get back to you. # Actor input Schema ## `locations` (type: `array`): Cities to search. Enter one per line. Accepted formats: City, State (New York, NY) — City, State, Zip (Austin, TX 78701) — full address (456 Oak Ave, Chicago, IL 60601). At least one location or zip code is required. ## `zipCodes` (type: `array`): US zip codes to search. Enter one per line (e.g. 10001). City and state are resolved automatically for each zip. ## `moveInDate` (type: `string`): Earliest move-in date (YYYY-MM-DD). Applied to all locations. Leave blank to search without a date filter. ## `moveOutDate` (type: `string`): Latest move-out date (YYYY-MM-DD). Use with Move-in date to target a specific rental window. Optional. ## `minBudget` (type: `integer`): Skip listings priced below this amount per month. Leave blank for no minimum. ## `maxBudget` (type: `integer`): Skip listings priced above this amount per month. Leave blank for no maximum. ## `maxItems` (type: `integer`): Maximum listings to collect per location or zip code. If you search 3 locations at 50 items each, you get up to 150 results total. ## `requestTimeoutSecs` (type: `integer`): Per-request timeout in seconds. ## Actor input object example ```json { "locations": [ "New York, NY" ], "moveInDate": "2026-07-15", "moveOutDate": "2026-09-01", "minBudget": 1500, "maxBudget": 5000, "maxItems": 30, "requestTimeoutSecs": 30 } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "locations": [ "New York, NY" ], "moveInDate": "2026-06-01" }; // Run the Actor and wait for it to finish const run = await client.actor("data_api/furnishedfinder-scraper-cheap").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "locations": ["New York, NY"], "moveInDate": "2026-06-01", } # Run the Actor and wait for it to finish run = client.actor("data_api/furnishedfinder-scraper-cheap").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "locations": [ "New York, NY" ], "moveInDate": "2026-06-01" }' | apify call data_api/furnishedfinder-scraper-cheap --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=data_api/furnishedfinder-scraper-cheap", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "FurnishedFinder Scraper (Cheap)", "description": "FurnishedFinder rental extractor that pulls listings by city and move-in date, so you get price, availability, bedrooms, and amenities in one automated run.", "version": "0.0", "x-build-id": "zXXzf2Rg1bzED2ehN" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/data_api~furnishedfinder-scraper-cheap/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-data_api-furnishedfinder-scraper-cheap", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/data_api~furnishedfinder-scraper-cheap/runs": { "post": { "operationId": "runs-sync-data_api-furnishedfinder-scraper-cheap", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/data_api~furnishedfinder-scraper-cheap/run-sync": { "post": { "operationId": "run-sync-data_api-furnishedfinder-scraper-cheap", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "locations": { "title": "Locations", "type": "array", "description": "Cities to search. Enter one per line. Accepted formats: City, State (New York, NY) — City, State, Zip (Austin, TX 78701) — full address (456 Oak Ave, Chicago, IL 60601). At least one location or zip code is required.", "items": { "type": "string" } }, "zipCodes": { "title": "Zip codes", "type": "array", "description": "US zip codes to search. Enter one per line (e.g. 10001). City and state are resolved automatically for each zip.", "items": { "type": "string" } }, "moveInDate": { "title": "Move-in date", "type": "string", "description": "Earliest move-in date (YYYY-MM-DD). Applied to all locations. Leave blank to search without a date filter." }, "moveOutDate": { "title": "Move-out date", "type": "string", "description": "Latest move-out date (YYYY-MM-DD). Use with Move-in date to target a specific rental window. Optional." }, "minBudget": { "title": "Min monthly budget (USD)", "minimum": 0, "type": "integer", "description": "Skip listings priced below this amount per month. Leave blank for no minimum." }, "maxBudget": { "title": "Max monthly budget (USD)", "minimum": 0, "type": "integer", "description": "Skip listings priced above this amount per month. Leave blank for no maximum." }, "maxItems": { "title": "Max items per location", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum listings to collect per location or zip code. If you search 3 locations at 50 items each, you get up to 150 results total.", "default": 30 }, "requestTimeoutSecs": { "title": "Request timeout (seconds)", "minimum": 5, "maximum": 120, "type": "integer", "description": "Per-request timeout in seconds.", "default": 30 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```