Agoda Prices Scraper — Hotel Rates & Availability by Date

Agoda prices scraper for real stays: give a destination or a list of hotels, a check-in date, nights and guests, and get every property's cheapest rate as clean rows — agoda hotel prices per night and for the whole stay, with and without taxes, the cancellation term, rooms left, stars, guest score and coordinates. It reads the same search answer agoda.com's own results page reads, so the numbers match what a traveller sees — a hotel rate scraper that returns Agoda's structured data rather than a rendered page. Use it as an agoda scraper for market research, as a hotel price comparison feed next to the Google Hotels and Booking.com actors below, or as the agoda api you were looking for: no key, no browser, pay per priced hotel.

Last verified working: 2026-08-29.

What the Agoda prices scraper returns

One hotel row per property Agoda prices for your stay:

• Price — price_nightly (per room per night, before taxes — Agoda's default display price), price_nightly_with_taxes, price_total and price_total_with_taxes for the whole booking, crossed_out_price when a discount is shown, the currency you asked for.
• Terms — cancellation (FreeCancellation, NonRefundable, SpecialConditions), free_cancellation, free_cancellation_until, breakfast_included, the raw benefit_ids, available_rooms at that rate, supplier_id, payment_model.
• Property — hotel_id, hotel_name, url, property_type, stars, review_score and review_count across every source Agoda aggregates, agoda_score and agoda_review_count from Agoda's own reviews, city, city_id, area, country, country_code, latitude, longitude.
• Stay — check_in, check_out, nights, adults, children, rooms, plus rank (position in the destination's results under sort), mode, query, locale, price_source and fetched_at.

Named properties can add a price calendar: one calendar row per check-in date Agoda has a price for, with price_nightly, price_total, its trend flag (Low, Normal, High), rank_in_window and cheapest_in_window. Every input also writes a free status row (target, mode, status, hotels, sold_out_hotels, filtered, pages, calendar_days, duplicates, error).

Why this Agoda scraper instead of the page

Agoda's results page loads prices asynchronously and re-polls its search until every property is priced — a browser-based scraper waits, scrolls and still misses the last poll. This actor calls the search endpoint with the synchronous flag Agoda's own client eventually sets, so one request returns 45 priced properties with the fields above already structured. Named hotels use Agoda's single "extra property" slot: one 3 KB answer per hotel, no page read. Two facts that matter for your data:

1. Sold-out is not a price. A property Agoda lists but cannot price for your stay comes back with sold_out: true and every price empty. Those rows are free and hidden unless you ask for them, so a price list stays a price list.
2. A throttle is never a "no results". When Agoda refuses a session the actor rotates the proxy session and retries; if every attempt is refused the input is reported as an error, not as an empty destination. An unknown destination id fails in one call with Agoda's own message.

Agoda hotel prices by destination

Put a city, area or country in locationQueries — or Agoda's numeric city id, or a search URL copied from agoda.com — and set the stay:

{
  "locationQueries": ["Lisbon", "Bangkok"],
  "checkIn": "30 days",
  "nights": 2,
  "adults": 2,
  "currency": "USD",
  "sortBy": "price_low",
  "maxHotelsPerQuery": 100
}

Each destination is resolved through Agoda's own autocomplete (the best match wins; put the country in the text for ambiguous names), then paged 45 properties at a time in sortBy order until maxHotelsPerQuery priced hotels have been collected. maxHotelsPerQuery: 0 takes every property Agoda lists for the stay — a capital runs to a few thousand rows, so set the cap for anything you schedule. The rank column is the position in Agoda's order for that sort, which is also how the cap cuts.

Which sort orders does the scraper support?

best_match (Agoda's ranking, the default), price_low (cheapest first — Agoda only sorts price ascending), guest_rating (highest review score first) and secret_deals. Sort only applies to destination searches; named properties are priced on their own.

Agoda hotel rates for named hotels

Name the properties with startUrls (property pages), hotelIds (Agoda's numeric ids, the fastest) or hotelNames (resolved through the autocomplete):

{
  "hotelIds": ["6988894", "63820"],
  "hotelNames": ["Tivoli Avenida Liberdade Lisbon"],
  "checkIn": "2026-10-10",
  "nights": 3,
  "adults": 2,
  "rooms": 1,
  "currency": "EUR",
  "calendarDays": 30
}

Each property costs one small request. A URL, its id and its name are one property: the run delivers it once and the later inputs report duplicates: 1. When a named property has no rate for the stay, its status row says sold_out; when Agoda does not know the id, not_found.

What is the price calendar?

With calendarDays: N the actor also reads Agoda's price-trend chart for each named property: the per-night price for up to 60 check-in dates from checkIn, at your length of stay and occupancy, each flagged Low, Normal or High by Agoda. Dates the chart has no cached price for are skipped (and free), so the calendar is sparse on quiet properties and dense on busy ones — it is a "when is it cheap" signal, not a guarantee of availability on every date. rank_in_window: 1 marks the cheapest date returned.

Filters that run before billing

• maxPrice — keep only hotels whose price_nightly is at or under this amount in your currency.
• minStars — keep only properties with at least this star rating (unrated properties are dropped when set).
• minReviewScore — keep only properties with at least this guest score out of 10.
• freeCancellationOnly — keep only hotels whose cheapest rate is free to cancel.

Every filter runs on the actor before the charge call, so a hotel a filter removes is never billed. A daily "anything in Lisbon under 60 with free cancellation" schedule costs nothing on days without a match; the status row still reports how many were filtered. includeSoldOut writes the unpriced properties too (free), which is useful for occupancy tracking.

What does one run cost?

Pay per event, only for what is delivered:

Event	Price	What it is
hotel	$0.004	One priced property for the stay
calendar_day	$0.002	One priced check-in date of a property's calendar

Sold-out properties, filtered hotels and status rows are free. Every property is billed once per run however many inputs reach it. Examples at list price: 100 hotels in a city, $0.40; a comp set of 20 named hotels every morning, $0.08 a day; the same 20 with a 30-day calendar, roughly $0.08 + 20 × (priced dates × $0.002). Runs use Apify Proxy datacenter sessions, which are included in your Apify plan; the endpoint tolerates about one request per second per IP, and a 45-property page is under 100 KB.

Input

Field	What it does
locationQueries	Destinations: names ("Lisbon"), Agoda city ids ("16364") or agoda.com search URLs. One search each.
startUrls	Agoda property pages (priced one by one) or search-result URLs (treated as destinations).
hotelIds	Agoda numeric property ids — the fastest way to price a known list.
hotelNames	Property names, resolved through Agoda's autocomplete; the best match is priced.
checkIn	YYYY-MM-DD or relative ("30 days", "6 weeks", "tomorrow") so schedules never go stale. Past dates are refused.
nights	Length of stay, 1-30.
adults, children, childAges, rooms	Occupancy the price is quoted for; ages 0-17, one per child.
currency	ISO code for every price (USD, EUR, GBP, THB, JPY…).
sortBy	Destination result order: best_match, price_low, guest_rating, secret_deals.
maxHotelsPerQuery	Priced properties per destination, in sortBy order; 0 = all. The main cost control.
maxPrice	Keep hotels at or under this nightly price; 0 = no limit. Filters before billing.
minStars	Keep properties with at least this star rating; 0 = any.
minReviewScore	Keep properties with at least this guest score (0-10); 0 = any.
freeCancellationOnly	Keep only free-cancellation rates.
includeSoldOut	Also write unpriced properties (free rows with sold_out: true).
calendarDays	Named properties only: read the price calendar for this many check-in dates (0-60).
locale	Agoda locale for names and areas (en-us, de-de, ja-jp…).
sessions, perIp	Parallel proxy sessions and the pace of each.
proxyConfiguration	Apify Proxy; datacenter is enough for this endpoint.

Output example

{
  "type": "hotel",
  "mode": "destination",
  "query": "Lisbon",
  "locale": "en-us",
  "hotel_id": "13505436",
  "hotel_name": "Help Yourself Hostels - Restelo",
  "url": "https://www.agoda.com/help-yourself-hostels-restelo/hotel/all/lisbon-pt.html",
  "property_type": "Hotel",
  "stars": 2.0,
  "review_score": 6.8,
  "review_count": 120,
  "agoda_score": 6.5,
  "agoda_review_count": 31,
  "city": "Lisbon",
  "city_id": 16364,
  "area": "Belem",
  "country": "Portugal",
  "country_code": "PT",
  "latitude": 38.6997,
  "longitude": -9.2079,
  "check_in": "2026-09-28",
  "check_out": "2026-09-29",
  "nights": 1,
  "adults": 2,
  "children": 0,
  "rooms": 1,
  "currency": "USD",
  "price_nightly": 44.71,
  "price_nightly_with_taxes": 60.67,
  "price_total": 44.71,
  "price_total_with_taxes": 60.67,
  "crossed_out_price": null,
  "available_rooms": 1,
  "cancellation": "FreeCancellation",
  "free_cancellation": true,
  "free_cancellation_until": null,
  "breakfast_included": false,
  "benefit_ids": [6, 95, 230, 231],
  "supplier_id": 332,
  "payment_model": "MerchantCommission",
  "sold_out": false,
  "rank": 46,
  "sort": "price_low",
  "price_source": "search",
  "fetched_at": "2026-08-29T11:20:04+00:00"
}

Dataset views: Hotels (every priced row in result order), Cheapest first (priced hotels by price_nightly), Price calendar (calendar rows with trend, rank_in_window, cheapest_in_window) and Status (target, mode, status, hotels, sold_out_hotels, filtered, pages, calendar_days, duplicates, error). The run's key-value store carries a SUMMARY record with the totals delivered, charged, filtered, sold out and failed, plus HTTP stats.

How to run the Agoda prices scraper from code

Python

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("kestrel/agoda-prices-scraper").call(run_input={
    "locationQueries": ["Lisbon"],
    "checkIn": "30 days", "nights": 2, "adults": 2, "currency": "EUR",
    "sortBy": "price_low", "maxHotelsPerQuery": 50, "freeCancellationOnly": True,
})
rows = [r for r in client.dataset(run["defaultDatasetId"]).iterate_items() if r["type"] == "hotel"]
for r in rows[:5]:
    print(r["rank"], r["hotel_name"], r["price_nightly"], r["currency"], r["cancellation"])

JavaScript

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' });
const run = await client.actor('kestrel/agoda-prices-scraper').call({
    hotelIds: ['6988894', '63820'], checkIn: '2026-10-10', nights: 3, adults: 2, currency: 'USD', calendarDays: 30,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
const cheapest = items.filter(r => r.type === 'calendar' && r.cheapest_in_window);
console.log(cheapest.map(r => [r.hotel_name, r.check_in, r.price_nightly]));

curl

curl -X POST "https://api.apify.com/v2/acts/kestrel~agoda-prices-scraper/run-sync-get-dataset-items?token=<YOUR_APIFY_TOKEN>&timeout=300" \
  -H "Content-Type: application/json" \
  -d '{"locationQueries": ["Bangkok"], "checkIn": "45 days", "nights": 1, "adults": 2, "currency": "THB", "maxHotelsPerQuery": 45, "minReviewScore": 8}'

Integrations: n8n, Make, MCP and AI agents

• n8n / Make / Zapier — call the actor with an HTTP Request node (run-sync-get-dataset-items, JSON body as above, a 300 s timeout) on a Schedule; keep checkIn relative so the workflow never goes stale. Filter on type first, then compare price_nightly with yesterday's value in your sheet or database to build a price-drop alert.
• MCP and AI agents — the actor is available through Apify's MCP server and to Apify AI, so an agent can ask for "the ten cheapest free-cancellation hotels in Lisbon next month" and receive these rows; the input and output schemas above are what the agent reads.
• Sheets, BI, webhooks — every run's dataset exports as JSON, CSV or Excel; add a webhook on run success to push new prices where they need to go.

Hotel price comparison and other uses for the data

• Hotel price comparison across channels — run the same stay through this actor, the Google Hotels Prices Scraper (every booking site's rate per hotel) and the Booking.com Reviews Scraper's sibling data, and see where Agoda undercuts.
• Rate parity — join on hotel_name with the Hotel Rate Parity Checker to flag OTAs cheaper than the official site.
• Agoda price tracker — schedule a destination search daily with relative dates; hotel_id is the stable join key and fetched_at the timestamp, so a month of runs is a price history per property — hotel price tracking without a rate-shopping subscription.
• Cheapest hotels on Agoda — sortBy: price_low with maxHotelsPerQuery: 20 is a twenty-row answer to "what is the cheapest place to sleep in Bangkok next Friday", refreshed every morning for a few cents.
• Market snapshots — maxHotelsPerQuery: 0 with includeSoldOut: true gives the whole inventory for a date: how many properties are priced, at what median, and how many are sold out — an occupancy proxy for a city.
• Revenue management — a comp set as hotelIds every morning with calendarDays: 60 shows every competitor's cheapest dates next to your own.

FAQ

Are these the prices a guest sees on Agoda?

Yes — for the same stay, currency and occupancy. price_nightly is Agoda's default display price (per room per night, before taxes and fees); price_total_with_taxes is what the booking would cost. Agoda personalises some discounts for logged-in members and app users; this actor prices as a logged-out visitor, the same view Google and metasearch engines get.

How many hotels can one run collect?

As many as Agoda lists for the stay: a large city returns one to three thousand properties at 45 per page. maxHotelsPerQuery caps that per destination (its default is 45, one page) and status.pages tells you how many pages were read. Runs are paced at about one request per second per session; four sessions read roughly 180 properties a second of wall time.

Can I get room-level rates?

The row carries the cheapest rate Agoda would show on the property card — one room type, one supplier — with its cancellation term, benefits and rooms left. Agoda room prices by room type (the full grid) are not part of this actor; ask on the Issues tab if you need them and say how many properties you price a day.

Does it work for apartments, hostels and resorts?

Yes: property_type tells them apart, and stars are empty for unrated properties. Filters like minStars drop unrated ones by design; use minReviewScore to rank hostels and apartments instead.

Why is a property sold out in one run and priced in the next?

Availability is per stay. Change the dates, the number of nights or the occupancy and Agoda's answer changes with it. The Tivoli Avenida Liberdade, for example, has no rate for one specific night but a price calendar full of other dates — that is exactly what calendarDays is for.

Which currencies and locales are supported?

Any ISO currency Agoda quotes in (USD, EUR, GBP, THB, JPY, AUD, SGD…), converted at Agoda's own rate. locale changes names and area labels (de-de, ja-jp, th-th…), not the prices.

What happens when Agoda throttles the run?

The session's IP is rotated and the request retried with back-off; the input is only reported as an error when every attempt was refused. Nothing is billed for an errored input, and the run only fails outright when every input failed.

Is scraping Agoda prices legal?

The actor reads public, logged-out price listings — the same data Agoda publishes to search engines and metasearch partners — and stores no personal data. Using that data for price comparison, market research and revenue management is a normal business use; check Agoda's terms and your local law before republishing prices commercially, respect the site with sensible pacing, and do not use the data to interfere with Agoda's service.

Related scrapers

Prices are one side of a booking decision. These read the rest of it and share the same pay-per-delivered-row billing:

• Agoda Reviews Scraper — every guest review of an Agoda property with separate positives and negatives.
• Google Hotels Prices Scraper — hotel prices and every booking site's rate for a stay.
• Hotel Rate Parity Checker — one row per property with every source side by side and the parity math done.
• Hotel Price Tracker — the lowest Google Hotels rate per property and date over a window, for daily schedules.
• Booking.com Reviews Scraper — Booking.com guest reviews by URL, name or id.

All of them bill per delivered row, never charge for rows a filter or a spending limit removed, and write an Apify dataset you can export to CSV, Excel or JSON.