Airbnb Scraper & Airbnb API — Listings, Prices, Reviews, Calendar & Hosts

Airbnb scraper and Airbnb API for Airbnb listings and Airbnb data: nightly prices, reviews, calendar availability, host portfolios and Experiences for $0.0005 per record ($0.50 per 1,000). Search by Airbnb URL, map bounding box, room URL or host ID and get flat, structured JSON with no API key, no browser and no per-run minimum. Empty and failed runs bill no records.

Built for short-term rental (STR) analytics, dynamic pricing engines, property underwriting and travel market research. Works from the Apify Console, the REST API, the Python and JavaScript clients, and as a tool for AI agents over MCP.

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⚡ Why this Airbnb scraper

• $0.0005 per record, every mode. Listings, room details, reviews, calendar months, host portfolio items and Experiences all bill at the same flat rate. 1,000 listings cost about fifty cents.
• No record charges for empty or failed runs. You pay only for rows that actually land in the dataset, plus the small actor start fee. Listings that Airbnb repeats across result pages are saved and billed once.
• Whole searches, not just page one. Searches page through every result page and split big areas into smaller map areas with the same filters until maxResults unique listings are found (up to 5,000).
• Five ways in. Search URL, map bounding box, room URL, host ID or Experience place name. Mix and match across runs.
• Seven modes, one actor. Listings, room details, reviews, calendar, host portfolios and Experiences without juggling separate tools.
• Clean, flat output. One record per row with a record_type tag, ready for spreadsheets, BI dashboards, SQL or LLM and RAG pipelines.
• Residential proxy on by default. Airbnb fingerprints datacenter IPs hard; the default residential proxy keeps results flowing, with automatic IP rotation and retries on room pages.

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👥 Who uses this

• STR analytics and revenue managers tracking supply, nightly rates and occupancy proxies in a market.
• Dynamic pricing tools feeding live comparable listings into a pricing engine.
• Property investors and underwriters comping a neighborhood before buying or converting a unit.
• Travel agencies and relocation services surfacing options for clients in seconds.
• Market researchers and journalists measuring shifts in supply, prices, Superhost share and host concentration.
• AI agents that need live Airbnb data as a tool call rather than a browser session.

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📦 What you get

Every record carries a record_type field: listing, room, review, calendar, host_listing, experience, plus info and error rows for diagnostics. The main fields per record type:

Field	Type	Present on	Meaning
room_id, room_url	string	listing, room, calendar, host_listing	Airbnb room ID and canonical airbnb.com/rooms/<id> URL
title	string	listing	Card title with property type and area, e.g. "Apartment in Lisbon"
name	string	listing, room, host_listing	Listing name set by the host
room_type	string	room, host_listing	Entire home/apt, Private room, Shared room or Hotel room
person_capacity	number	room	Maximum guests
bedrooms, beds, bathrooms	number	listing	Layout shown on the search card
rating, review_count	number	listing, room, host_listing	Average rating and number of reviews
is_superhost	boolean	listing, room, host_listing	Superhost host. A search card shows one badge, so it is left out when the card shows Guest favorite
is_guest_favorite	boolean	listing, room	Guest favorite listing
free_cancellation	boolean	listing	Free cancellation offered
price_total	number	listing, room	Total for the stay: your dates, or 5 nights when the search URL has no dates
price_per_night, price_per_night_original	number	listing (room: price_per_night)	Nightly price after and before discounts (price_total ÷ nights)
price_unit_qualifier	string	listing, room	What the price covers, e.g. "for 3 nights"
price_currency_symbol, price_currency	string	listing, room (price_currency: room)	Currency symbol of the prices; ISO code of the room quote
latitude, longitude	number	listing, room, experience	Coordinates for mapping and geofencing
host_id, host_url	string	room, host_listing (host_url: room)	Host ID and profile URL
description	string	room	Listing description
images	array	listing, room, host_listing, experience	Photo URLs
reviews, calendar	array	room, calendar	Embedded reviews and month-by-month availability
review_id, rating, comment, language, created_at, reviewer_name, reviewer_location	mixed	review	One review per row
experience_id, place, title, duration	string	experience	Experience ID, the place you searched, title and duration
scraped_at	string	all	ISO 8601 UTC timestamp

Fields that Airbnb does not return for a given listing are omitted rather than filled with placeholders, so downstream schemas stay honest.

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📥 Input and modes

Pick a mode, then fill in the inputs for that mode. Every field on the form has inline help.

Mode	Required	Optional
search_by_url	searchUrl	currency, language, maxResults
search_by_bbox	neLat, neLng, swLat, swLng	checkIn, checkOut, priceMin, priceMax, placeType, amenities, freeCancellation, zoom, currency, language, maxResults
room_details	roomUrls	checkIn, checkOut, adults, currency, language
room_reviews	roomUrls	language, maxResults
room_calendar	roomUrls	none
host_listings	hostId	currency, language
experience_search	experiencePlace (or experiencePlaceId)	checkIn, checkOut, currency, language, maxResults

Search by URL is the fastest way to reproduce exactly what you see on airbnb.com: apply dates, price, amenity and map filters in your browser, copy the URL and paste it in. Location segments such as airbnb.com/s/Paris--France/homes or New-York--NY--United-States are honored. Airbnb shows about 250 listings per search, so for a larger maxResults the actor splits the area into smaller map areas with the same filters and keeps going.

Search by bounding box takes north-east and south-west coordinates plus optional dates, price range, place type, amenity IDs and a free-cancellation flag. Set both checkIn and checkOut if you want nightly prices back.

Room details accepts up to 100 room URLs per run, fetches them in parallel and returns the listing page: name, description, room type, guest capacity, rating, host ID, coordinates, photos, embedded reviews and calendar, plus a price quote for your dates and guest count. When those dates are not available the listing still ships without the price fields, so you keep name, rating, host and photos.

Room reviews and room calendar target the same URLs and return one row per review, or one row per room with a month-by-month calendar array.

Host listings takes the numeric host ID from airbnb.com/users/show/<id> and returns every active listing in that host's portfolio with name, room type, rating, review count, Superhost flag and cover photo.

Experiences searches Airbnb Experiences for a city or place name such as "Amsterdam".

Example input for a map search:

{
  "mode": "search_by_bbox",
  "neLat": 38.78,
  "neLng": -9.10,
  "swLat": 38.69,
  "swLng": -9.23,
  "checkIn": "2026-06-10",
  "checkOut": "2026-06-15",
  "placeType": "Entire home/apt",
  "currency": "EUR",
  "maxResults": 500
}

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📤 Sample output

A listing row from a search:

{
  "record_type": "listing",
  "room_id": "12345678",
  "room_url": "https://www.airbnb.com/rooms/12345678",
  "title": "Apartment in Lisbon",
  "name": "Bright 2BR apartment near Alfama",
  "bedrooms": 2,
  "beds": 2,
  "bathrooms": 1,
  "rating": 4.89,
  "review_count": 212,
  "is_superhost": true,
  "is_guest_favorite": false,
  "free_cancellation": false,
  "price_per_night": 138,
  "price_per_night_original": 155,
  "price_total": 690,
  "price_unit_qualifier": "for 5 nights",
  "price_currency_symbol": "€",
  "latitude": 38.7139,
  "longitude": -9.1334,
  "images": ["https://a0.muscache.com/im/pictures/....jpg"],
  "scraped_at": "2026-08-29T05:02:22+00:00"
}

A review row:

{
  "record_type": "review",
  "room_url": "https://www.airbnb.com/rooms/12345678",
  "review_id": "987654321",
  "rating": 5,
  "comment": "Great location and a very responsive host.",
  "language": "en",
  "created_at": "2026-05-02T10:14:00Z",
  "reviewer_name": "Anna",
  "reviewer_location": "Berlin, Germany",
  "scraped_at": "2026-08-29T05:02:22+00:00"
}

Use the dataset tabs (Overview, Hosts, Full Data) in the Console to browse, or export as JSON, CSV, Excel, XML or RSS from the dataset.

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💵 Pricing — pay only for delivered records

Event	Price	When
listing-scraped	$0.0005	per search result (URL or map search)
room-details-scraped	$0.0005	per full room detail page
review-scraped	$0.0005	per review row
calendar-month-scraped	$0.0005	per calendar month returned
host-listing-scraped	$0.0005	per host portfolio item
experience-scraped	$0.0005	per Experience result

Worked example. Scraping 1,000 listings from a Lisbon search URL bills 1,000 × $0.0005 = $0.50. Pulling full room details for 200 of them adds 200 × $0.0005 = $0.10. A run that returns zero rows bills zero record events. The only fixed cost is the Apify actor start fee of $0.00005 per GB of memory, about $0.0002 per run at the default 4 GB, so the 1,000-listing run lands at roughly $0.50 all in.

Use maxResults to cap large searches and avoid surprises. Apify's free plan credit is enough for several thousand records per month.

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❓ FAQ

Does Airbnb have an official API?

Airbnb has no public data API. The partner API is restricted to approved property management software. This actor reads the same public listing, search, review and calendar pages a visitor sees and turns them into structured JSON, so you get Airbnb data without an API key or a partner agreement.

How much does it cost to scrape 1,000 Airbnb listings?

$0.50 in record events plus about $0.0002 for the actor start. 10,000 listings cost about $5. Room details, reviews, calendar months and host listings bill at the same $0.0005 per record.

Can I get Airbnb prices for specific dates?

Yes. In search_by_bbox set checkIn and checkOut to receive nightly and total prices in your chosen currency. In room_details set the dates and adults to get a live quote for that exact stay. search_by_url picks dates up from the URL you paste.

How fast is it and what are the limits?

Searches page through every result page Airbnb shows (about 250 listings per search) and, when you ask for more, split the area into smaller map areas with the same filters until maxResults unique listings are found (up to 5,000) or the area runs out of listings. Room details accept up to 100 URLs per run and fetch 8 pages in parallel with up to 5 retries and a fresh residential IP per retry. A 100-listing search typically finishes in well under a minute.

Is scraping Airbnb legal?

Scraping publicly available data is generally lawful in most jurisdictions, but you are responsible for how you use it. Do not collect personal data beyond what you need, respect Airbnb's terms and local privacy law (GDPR, CCPA), and consult a lawyer for commercial use at scale.

Which output formats can I export?

JSON, CSV, Excel, XML, HTML table and RSS, straight from the dataset in the Console or through the API. Every row is flat, so CSV opens cleanly in Excel or Google Sheets.

How does this compare to other Airbnb scrapers?

Most alternatives charge per result with different prices per mode, or bill by compute time so a blocked run still costs money. This actor bills $0.0005 for every record type, bills no records for empty or failed runs, and handles listings, room details, reviews, calendar, host portfolios and Experiences in one tool.

Why did some room URLs come back as error rows?

Airbnb applies aggressive anti-bot checks to room pages. When a page is blocked after all retries the actor returns the successful rows, an info row summarizing how many succeeded, and one error row per failed URL. Retry the failed URLs a few minutes later; failed rows are not billed.

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🤖 Use with AI agents and MCP

Add the actor as a tool in Claude, Cursor, VS Code, or any MCP-compatible agent through the Apify MCP server:

https://mcp.apify.com/?tools=fetch-actor-details,openclawai/airbnb-scraper

Your agent can then call openclawai/airbnb-scraper with the same input JSON shown above and read the dataset back as tool output. A step-by-step guide with prompts and agent recipes is at datapika.com/actors/airbnb-scraper.

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🔌 Integrations

• REST API: POST https://api.apify.com/v2/acts/openclawai~airbnb-scraper/run-sync-get-dataset-items?token=YOUR_TOKEN with the input JSON as the body.
• Python: apify-client package, client.actor("openclawai/airbnb-scraper").call(run_input={...}).
• JavaScript / TypeScript: apify-client package, client.actor("openclawai/airbnb-scraper").call({...}).
• No-code: Apify integrations for Zapier, Make, n8n, Google Sheets, Slack and webhooks work out of the box.
• Scheduling: run on a cron schedule from the Console to track prices and availability over time.

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⚠️ Notes

• For bounding-box search to return prices, set both checkIn and checkOut.
• Airbnb rate-limits datacenter IPs aggressively. Leave the default residential proxy on.
• Amenity IDs for search_by_bbox are the numeric values in Airbnb search URLs (amenities%5B%5D=4). Apply the amenity filter on airbnb.com and read the IDs from the URL.
• Use maxResults to cap large queries and avoid billing surprises.

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⚖️ Legal and ethics

This actor collects only publicly visible information and is intended for market research, analytics and personal use. It does not bypass logins or access private data. You are responsible for complying with Airbnb's terms of service and with applicable data protection laws when storing or redistributing scraped data, especially reviewer names and host details.

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📝 Changelog

Recent fixes: searches now page through every result page and split big areas to reach maxResults (search by URL used to stop at the first 40 listings), listings repeated across pages are saved and billed once, listing rows carry coordinates and true nightly prices (search cards show the stay total), host portfolio rows carry name, rating and photo, and room details carry name, description, host ID and a numeric price quote. Earlier: search by URL honors the location in the URL path, room details retry up to 5 times with a fresh IP and detect challenge pages, batch runs return partial results plus an info summary instead of failing, and unavailable dates return the listing with price_unavailable_reason instead of an error. Full version history ships with the actor as CHANGELOG.md.