# FurnishedFinder $1💰 Listings, Amenities & Reviews (`abotapi/furnishedfinder-scraper`) Actor From $1/1K. Scrape furnishedfinder.com listings by city or URL. Extract structured data including price, beds, baths, occupancy, amenities, photos, location, square footage, ratings, reviews, utilities, house rules, and fees. Fast and reliable via the site's data API. - **URL**: https://apify.com/abotapi/furnishedfinder-scraper.md - **Developed by:** [AbotAPI](https://apify.com/abotapi) (community) - **Categories:** Travel, Developer tools, E-commerce - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $1.00 / 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 a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. 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.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.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/platform/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 ## Furnished Finder Scraper Scrape monthly furnished rental listings from Furnished Finder at scale. Search by city or paste URLs, and the actor walks every result page and returns clean, structured records: price, bedrooms, bathrooms, sleeps, amenities, photos, coordinates, square footage, ratings, reviews, utilities, house rules and fees. Built on the site's own data API, so it is fast, cheap, and resilient to page redesigns. ### Why This Scraper? - Up to 30+ fields per listing, including square footage, average rating, review count, individual guest reviews, utilities included, house rules, fees and a full amenity list. - Two input modes: search by free-text city ("Houston, TX") or paste search and property URLs. - Forward auto-pagination, 50 listings per page, with an overall listing cap. - Verified filters that actually narrow results: price range, property type, minimum bedrooms, minimum bathrooms. - Optional detail enrichment so you only pay for the depth you need. - Concurrent enrichment with per-record output, so a stopped run still keeps everything finished so far. ### Data You Get > Sample shape: values are illustrative placeholders, not from a live listing. | Field | Example | | --- | --- | | id | `00000001_1` | | url | `https://www.furnishedfinder.com/property/00000001_1` | | name | `Sample Furnished Rental Near Downtown` | | propertyType | `House` | | propertyTypeClass | `entire_unit` | | priceValue | `2000` | | priceFormatted | `$2,000/month` | | priceCurrency | `USD` | | bedroomCount | `2` | | bathroomCount | `1` | | totalSleeps | `4` | | laundryType | `In-Unit W/D` | | squareFootage | `1200` | | avgRating | `4.5` | | totalReviewCount | `2` | | reviews | `[{ "reviewerName": "Jane D", "starRating": 5, "submissionDate": "Jan 01, 2026", "title": "Great stay", "text": "Clean and comfortable.", "reply": null }]` | | utilitiesIncluded | `true` | | minimumStayDays | `30` | | city | `Houston` | | state | `Texas` | | latitude | `29.0000` | | longitude | `-95.0000` | | isAvailableNow | `true` | | availableOnDate | `Available` | | amenities | `["airConditioning", "wifi", "dishwasher"]` | | photoCount | `12` | | scrapedAt | `2026-01-01T00:00:00.000Z` | ### How to Use Search a single city (full details): ```json { "mode": "search", "locations": ["Houston, TX"], "maxPages": 5, "fetchDetails": true, "proxy": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"], "apifyProxyCountry": "US" } } ```` Search several cities with filters: ```json { "mode": "search", "locations": ["Seattle, WA", "Denver, CO", "Austin, TX"], "minPrice": 1000, "maxPrice": 2500, "minBedrooms": 2, "propertyTypeClass": "entire_unit", "maxListings": 300 } ``` Paste a search URL and auto-paginate: ```json { "mode": "url", "urls": ["https://www.furnishedfinder.com/housing/us--tx--houston"], "maxPages": 10 } ``` Scrape specific property URLs: ```json { "mode": "url", "urls": [ "https://www.furnishedfinder.com/property/00000001_1", "https://www.furnishedfinder.com/property/00000002_1" ], "fetchDetails": true } ``` ### Input Parameters | Parameter | Type | Default | Description | | --- | --- | --- | --- | | mode | string | `search` | `search` (cities + filters) or `url` (paste URLs). | | locations | array | `["Houston, TX"]` | Cities for search mode. Free text, `City, State`, or a `us--tx--houston` slug. | | urls | array | (empty) | Search or property URLs for URL mode. | | propertyTypeClass | string | `any` | `any`, `entire_unit`, or `room`. | | minPrice | integer | (none) | Minimum monthly rent in USD. | | maxPrice | integer | (none) | Maximum monthly rent in USD. | | minBedrooms | integer | (none) | Minimum bedroom count. | | minBathrooms | integer | (none) | Minimum bathroom count. | | fetchDetails | boolean | `true` | Fetch full property details per listing. | | maxPages | integer | `5` | Result pages per city or search URL (50 listings each). | | maxListings | integer | `0` | Overall cap across all cities/URLs (0 = unlimited). | | proxy | object | Residential US | Proxy config. Residential US is required. | ### Output Example > Sample shape: values are illustrative placeholders, not from a live listing. ```json { "id": "00000001_1", "propertyId": "00000001", "unitId": "1", "url": "https://www.furnishedfinder.com/property/00000001_1", "name": "Sample Furnished Rental Near Downtown", "propertyType": "House", "propertyTypeClass": "entire_unit", "bedroomCount": 2, "bathroomCount": 1, "bathroomType": "Private Bath", "totalSleeps": 4, "laundryType": "In-Unit W/D", "priceFormatted": "$2,000/month", "priceValue": 2000, "priceCurrency": "USD", "latitude": 29.0000, "longitude": -95.0000, "city": "Houston", "state": "Texas", "encodedLocationName": "us--tx--houston", "isAvailableNow": true, "availableOnDate": "Available", "minimumStayInDays": 30, "amenities": ["airConditioning", "wifi", "dishwasher"], "photos": ["https://staticproperties.furnishedfinder.com/00000001/1/00000001_1_00000000-full.jpg"], "photoCount": 12, "description": "Full property description appears here when fetchDetails is on.", "neighborhoodDescription": "Neighborhood summary text.", "spaceDescription": "Space summary text.", "squareFootage": 1200, "avgRating": 4.5, "totalReviewCount": 2, "reviews": [ { "reviewId": "00000001", "reviewerName": "Jane D", "reviewerImage": "J", "starRating": 5, "title": "Great stay", "text": "Clean and comfortable, great communication.", "submissionDate": "2026-01-01", "reply": null } ], "utilitiesIncluded": true, "minimumStayDays": 30, "houseRules": [{ "name": "No smoking", "description": "Smoking is not allowed." }], "fees": [{ "type": "Cleaning", "amount": "$100" }], "detailAmenities": [{ "name": "Air Conditioning", "value": "airConditioning" }], "bedroomsDetail": [{ "title": "Bedroom 1", "type": "Queen Bed" }], "bathroomsDetail": [{ "title": "Bathroom 1", "type": "Full Bath" }], "searchLocation": "Houston, TX", "scrapedAt": "2026-01-01T00:00:00.000Z" } ``` ### Plan Requirement This actor needs Apify Residential proxy with country US. The site only accepts traffic from US residential connections, so data-centre IPs return zero results. Residential proxy is available on the Apify Starter plan and above. On the free plan the run will likely return no items; upgrade at https://apify.com/pricing to enable residential proxy access. # Actor input Schema ## `mode` (type: `string`): search = enter cities and filters. url = paste Furnished Finder search or property URLs. ## `locations` (type: `array`): Cities to scrape. Accepts free text ('Houston, TX', 'Houston'), 'City, State', or a Furnished Finder slug ('us--tx--houston'). One search box is built around each city. ## `propertyTypeClass` (type: `string`): Entire unit (whole place) or Room (private/shared room). Leave as Any for both. ## `minPrice` (type: `integer`): Minimum monthly rent. Leave empty for no minimum. ## `maxPrice` (type: `integer`): Maximum monthly rent. Leave empty for no maximum. ## `minBedrooms` (type: `integer`): Minimum bedroom count. Leave empty for any. ## `minBathrooms` (type: `integer`): Minimum bathroom count. Leave empty for any. ## `urls` (type: `array`): Paste Furnished Finder search URLs (/housing/us--tx--houston) or property URLs (/property/999116\_1). Multi-URL supported. ## `fetchDetails` (type: `boolean`): ON: each listing gets description, square footage, rating, review count, utilities, house rules, fees, full amenity list and bed/bath breakdown (one extra request per listing). OFF: faster, listing-card fields only. ## `fetchReviews` (type: `boolean`): ON: add a reviews array per listing (reviewer, star rating, date, text, landlord reply). Only applies when 'Fetch full property details' is ON, and only listings that have reviews cost an extra request. Turn OFF to keep details but skip reviews. ## `maxPages` (type: `integer`): How many result pages (50 listings each) to walk per city/search URL. ## `maxListings` (type: `integer`): Overall cap across all cities/URLs. 0 means no cap (bounded by max pages). ## `proxy` (type: `object`): Residential US is required. Free plans do not include residential proxy. ## Actor input object example ```json { "mode": "search", "locations": [ "Houston, TX" ], "propertyTypeClass": "any", "urls": [ "https://www.furnishedfinder.com/housing/us--tx--houston" ], "fetchDetails": true, "fetchReviews": true, "maxPages": 1, "maxListings": 0, "proxy": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "US" } } ``` # Actor output Schema ## `overview` (type: `string`): No description # 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 = { "mode": "search", "locations": [ "Houston, TX" ], "urls": [ "https://www.furnishedfinder.com/housing/us--tx--houston" ], "proxy": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "US" } }; // Run the Actor and wait for it to finish const run = await client.actor("abotapi/furnishedfinder-scraper").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 = { "mode": "search", "locations": ["Houston, TX"], "urls": ["https://www.furnishedfinder.com/housing/us--tx--houston"], "proxy": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], "apifyProxyCountry": "US", }, } # Run the Actor and wait for it to finish run = client.actor("abotapi/furnishedfinder-scraper").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 '{ "mode": "search", "locations": [ "Houston, TX" ], "urls": [ "https://www.furnishedfinder.com/housing/us--tx--houston" ], "proxy": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "US" } }' | apify call abotapi/furnishedfinder-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=abotapi/furnishedfinder-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "FurnishedFinder $1💰 Listings, Amenities & Reviews", "description": "From $1/1K. Scrape furnishedfinder.com listings by city or URL. Extract structured data including price, beds, baths, occupancy, amenities, photos, location, square footage, ratings, reviews, utilities, house rules, and fees. Fast and reliable via the site's data API.", "version": "1.0", "x-build-id": "0LMQrjAoprbqfDVki" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/abotapi~furnishedfinder-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-abotapi-furnishedfinder-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/abotapi~furnishedfinder-scraper/runs": { "post": { "operationId": "runs-sync-abotapi-furnishedfinder-scraper", "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/abotapi~furnishedfinder-scraper/run-sync": { "post": { "operationId": "run-sync-abotapi-furnishedfinder-scraper", "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", "required": [ "mode" ], "properties": { "mode": { "title": "Mode", "enum": [ "search", "url" ], "type": "string", "description": "search = enter cities and filters. url = paste Furnished Finder search or property URLs.", "default": "search" }, "locations": { "title": "Cities", "type": "array", "description": "Cities to scrape. Accepts free text ('Houston, TX', 'Houston'), 'City, State', or a Furnished Finder slug ('us--tx--houston'). One search box is built around each city.", "default": [ "Houston, TX" ], "items": { "type": "string" } }, "propertyTypeClass": { "title": "Property type", "enum": [ "any", "entire_unit", "room" ], "type": "string", "description": "Entire unit (whole place) or Room (private/shared room). Leave as Any for both.", "default": "any" }, "minPrice": { "title": "Min monthly price (USD)", "minimum": 0, "type": "integer", "description": "Minimum monthly rent. Leave empty for no minimum." }, "maxPrice": { "title": "Max monthly price (USD)", "minimum": 0, "type": "integer", "description": "Maximum monthly rent. Leave empty for no maximum." }, "minBedrooms": { "title": "Min bedrooms", "minimum": 0, "type": "integer", "description": "Minimum bedroom count. Leave empty for any." }, "minBathrooms": { "title": "Min bathrooms", "minimum": 0, "type": "integer", "description": "Minimum bathroom count. Leave empty for any." }, "urls": { "title": "URLs", "type": "array", "description": "Paste Furnished Finder search URLs (/housing/us--tx--houston) or property URLs (/property/999116_1). Multi-URL supported.", "items": { "type": "string" } }, "fetchDetails": { "title": "Fetch full property details", "type": "boolean", "description": "ON: each listing gets description, square footage, rating, review count, utilities, house rules, fees, full amenity list and bed/bath breakdown (one extra request per listing). OFF: faster, listing-card fields only.", "default": true }, "fetchReviews": { "title": "Include guest reviews", "type": "boolean", "description": "ON: add a reviews array per listing (reviewer, star rating, date, text, landlord reply). Only applies when 'Fetch full property details' is ON, and only listings that have reviews cost an extra request. Turn OFF to keep details but skip reviews.", "default": true }, "maxPages": { "title": "Max pages per city", "minimum": 1, "maximum": 500, "type": "integer", "description": "How many result pages (50 listings each) to walk per city/search URL.", "default": 1 }, "maxListings": { "title": "Max listings (0 = unlimited)", "minimum": 0, "type": "integer", "description": "Overall cap across all cities/URLs. 0 means no cap (bounded by max pages).", "default": 0 }, "proxy": { "title": "Proxy", "type": "object", "description": "Residential US is required. Free plans do not include residential proxy.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "US" } } } }, "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 } } } } } } } } } } ```