# Expedia Reviews Scraper ✈️ Hotel Ratings, Text & Sentiment (`factden/expedia-hotel-reviews-scraper`) Actor

Scrape Expedia hotel reviews at scale - guest ratings, full review text, sub-ratings, stay dates, traveler type, language & owner responses, plus LLM-ready markdown. Also accepts Hotels.com, Travelocity, Orbitz, Wotif, CheapTickets & ebookers URLs. Filter by date/rating; export JSON/CSV.

- **URL**: https://apify.com/factden/expedia-hotel-reviews-scraper.md
- **Developed by:** [Factden](https://apify.com/factden) (community)
- **Categories:** Travel, Business, AI
- **Stats:** 16 total users, 15 monthly users, 100.0% runs succeeded, 8 bookmarks
- **User rating**: 5.00 out of 5 stars

## Pricing

from $0.002 / review

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.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — 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

## Expedia Reviews Scraper

**Scrape Expedia hotel reviews at scale** - guest **ratings**, full **review text**, category **sub-ratings**,
**stay dates**, **traveler type**, **language**, and **hotel owner responses** - plus a per-review
**LLM-ready markdown** block. Paste one or more [Expedia](https://www.expedia.com) hotel URLs and export clean
**JSON, CSV, Excel, or via API**. No login, no Expedia API key.

> **One actor, all seven Expedia Group sites** - **Expedia, Hotels.com, Travelocity, Orbitz, Wotif,
> CheapTickets & ebookers.** Paste any of their hotel URLs and get the **same fields, same output schema**.
> A single actor replaces seven separate scrapers.

Runs on the Apify platform, so you get **scheduling**, a **REST API**, **webhooks & integrations**, **proxy
rotation**, and **run monitoring** out of the box - plus **incremental / since-date** runs so you only pull
what's new.

![Expedia hotel reviews - one row per review](https://raw.githubusercontent.com/factden/apify-actor-assets/main/expedia-hotel-reviews-scraper/02-reviews-overview.png)

### Supported sites - all 7 Expedia Group brands in one actor

This actor covers **every Expedia Group hotel brand** from one input. They share Expedia's backend, so the same
property resolves across brands and the **output schema is identical** no matter which brand URL you paste:

| Brand | Example hotel URL to paste |
|---|---|
| **Expedia** | `https://www.expedia.com/Las-Vegas-Hotels-Bellagio.h140596.Hotel-Information` |
| **Hotels.com** | `https://www.hotels.com/ho119566/` |
| **Travelocity** | `https://www.travelocity.com/...h140596.Hotel-Information` |
| **Orbitz** | `https://www.orbitz.com/...h140596.Hotel-Information` |
| **Wotif** | `https://www.wotif.com/...h140596.Hotel-Information` |
| **CheapTickets** | `https://www.cheaptickets.com/...h140596.Hotel-Information` |
| **ebookers** | `https://www.ebookers.com/...h140596.Hotel-Information` |

Hotels.com `/ho<id>/` links are **resolved automatically** to the global property. Mix brands freely in one run,
and use the **Review sources** filter to keep only certain brands' reviews (or leave it empty for the
cross-brand union).

### What does Expedia Reviews Scraper do?

It extracts **every public guest review** for any Expedia Group hotel you point it at, and returns a clean,
structured record per review - the overall **/10 rating**, the written **review text**, category
**sub-ratings** (cleanliness, service, room comfort, hotel condition, amenities, eco-friendliness), **stay
dates**, **traveler type**, **language**, **review photos**, and any **hotel owner response**. Alongside the
reviews it returns a **hotel aggregate**: average rating, recency-weighted rating, total review count, the full
1-5 **rating distribution**, and per-language / per-traveler-type counts.

### Why use Expedia Reviews Scraper?

- **Reputation & sentiment analysis** - track guest sentiment for your own or competitor hotels over time; every
  review carries structured sub-ratings and a sentiment-ready text block.
- **Competitor benchmarking** - pull rating distributions, category sub-scores and review volume per property to
  see exactly where a competitor wins or loses.
- **Market research** - analyze traveler types, languages, and what guests praise or complain about across a
  whole market or brand.
- **AI / RAG pipelines** - every review ships with a self-contained `markdownContent` block ready for
  vector-DB ingestion, so you can build a hotel-reviews chatbot or summarizer without any post-processing.
- **Hospitality tooling** - power owner-response tracking, guest-experience dashboards, or review-response SLAs.

### How to use Expedia Reviews Scraper

1. Open a hotel's page on Expedia (or any of the six other brands above) and copy the URL - it contains a
   `.h<number>.` segment, e.g. `.../Las-Vegas-Hotels-Bellagio.h140596.Hotel-Information`.
2. Paste one or more such URLs (any Expedia Group site) or bare property IDs into **Hotel URLs**.
3. (Optional) Set **Max reviews per hotel**, a **date range**, a **rating range**, a **sort order**, or
   **Review sources**.
4. Click **Start**, then download the results as **JSON, CSV, Excel**, or pull them from the **API**.

![Input tab - hotel URLs plus filters & limits](https://raw.githubusercontent.com/factden/apify-actor-assets/main/expedia-hotel-reviews-scraper/01-input-form.png)

### Input

| Field | Description |
|---|---|
| **Hotel URLs or property IDs** (`hotelUrls`) | Hotel-page URLs from any of the 7 brands (each with a `.h<id>.` segment), Hotels.com `/ho<id>/` URLs, **or bare property IDs** (`140596`). One per line. |
| **Max reviews per hotel** (`maxReviewsPerHotel`) | Cap per hotel (default 200). |
| **Sort reviews by** (`sortBy`) | `newest` (default), `oldest`, `highestRating`, `lowestRating`. Reviews are fetched newest-first; highest/lowest reorder the retrieved set. |
| **From / To date** (`fromDate` / `toDate`) | Keep only reviews in a `YYYY-MM-DD` range - ideal for **incremental / since-date** monitoring. |
| **Min / Max rating** (`minRating` / `maxRating`) | Keep only reviews within a 1-5 rating range (input scale is 1-5). |
| **Review sources** (`reviewSources`) | Which Expedia Group brands' reviews to return. Empty = all (cross-brand union); one = that brand only; several = that subset. |
| **Proxy** (`proxyConfiguration`) | Datacenter is enough; use residential for very large runs. |

#### Example input

```json
{
  "hotelUrls": [
    "https://www.expedia.com/Las-Vegas-Hotels-The-Venetian-Resort-Las-Vegas.h1443.Hotel-Information",
    "140596",
    "https://www.hotels.com/ho115902/",
    "https://www.travelocity.com/Las-Vegas-Hotels-Caesars-Palace.h41245.Hotel-Information",
    "https://www.orbitz.com/Las-Vegas-Hotels-The-Palazzo.h1769973.Hotel-Information"
  ],
  "maxReviewsPerHotel": 50,
  "sortBy": "newest",
  "fromDate": "2026-01-01",
  "minRating": 1,
  "maxRating": 5,
  "reviewSources": []
}
```

This example mixes an **Expedia URL**, a **bare property ID**, and **Hotels.com, Travelocity and Orbitz** URLs -
five different hotels across four brands - to show that any Expedia Group input is accepted. When you pass a bare
ID, `hotelName` comes back `null` (the name is read from a URL's descriptor slug, which an ID doesn't have).

### Output

The actor writes to **two datasets**:

- **Reviews** (the default dataset) - **one row per guest review**, with the hotel context
  (`hotelId` / `hotelName` / `hotelUrl` / `source`) merged onto every row.
- **Hotels** - **one row per hotel** with the aggregate: average rating, recency-weighted rating, total
  review count, rating distribution, category sub-ratings, coordinates and how many reviews were extracted.

The **Output** tab shows the Reviews dataset by default, plus an **AI ingest** view (the LLM-ready
`markdownContent` column) and the **Hotels** dataset. You can download any of them in **JSON, HTML, CSV, or
Excel**, or fetch them from the API (the reviews dataset also exposes `?view=aiIngest`).

**Hotels dataset** - one row per hotel with the full aggregate:

![Hotels - one row per hotel](https://raw.githubusercontent.com/factden/apify-actor-assets/main/expedia-hotel-reviews-scraper/04-hotel-overview.png)

**AI ingest view** - the self-contained, LLM-ready markdown for each review:

![AI ingest view - LLM-ready markdown](https://raw.githubusercontent.com/factden/apify-actor-assets/main/expedia-hotel-reviews-scraper/03-reviews-ai-ingest.png)

Here is a **real review row** from a run on the Bellagio (Las Vegas):

```json
{
  "hotelId": 140596,
  "hotelName": "Bellagio",
  "hotelUrl": "https://www.expedia.com/Las-Vegas-Hotels-Bellagio.h140596.Hotel-Information",
  "source": "expedia",
  "reviewId": "6a5163ef5acf8d54499c0073",
  "submittedAt": "2026-07-10T21:29:04Z",
  "overallRating": 10,
  "ratingLabel": "Exceptional",
  "reviewText": "Great as usual!",
  "subRatings": ["Cleanliness: 10", "Service: 10", "Hotel condition: 8", "Amenities: 10"],
  "verified": true,
  "reviewerName": "Alexey",
  "reviewerLocation": null,
  "checkInDate": "2026-07-05T00:00:00Z",
  "checkOutDate": "2026-07-10T00:00:00Z",
  "travelCompanions": ["Family"],
  "travelerCategories": ["Families"],
  "language": "en",
  "isMachineTranslated": false,
  "helpfulVotes": 0,
  "imagesCount": 0,
  "reviewPhotos": [],
  "ownerResponse": null,
  "roomTypeId": "314062401",
  "isAnonymous": false,
  "brandType": "Expedia",
  "markdownContent": "# Bellagio review (Expedia)\n\n**Rating:** 10/10 ★★★★★\n**Travelling as:** Family\n**Sub-ratings:** Cleanliness: 10; Service: 10; Hotel condition: 8; Amenities: 10\n\n## Review\nGreat as usual!"
}
```

...and the matching **hotel row** from the Hotels dataset:

```json
{
  "hotelId": 140596,
  "hotelName": "Bellagio",
  "hotelUrl": "https://www.expedia.com/Las-Vegas-Hotels-Bellagio.h140596.Hotel-Information",
  "source": "expedia",
  "brandName": "MGM",
  "structureType": "hotels",
  "latitude": 36.112488,
  "longitude": -115.17673,
  "avgOverallRating": 8.83,
  "halfLifeRating": 9.02,
  "totalReviewCount": 14700,
  "ratingDistribution": { "1": 523, "2": 512, "3": 1228, "4": 2529, "5": 9908 },
  "hotelSubRatings": ["Cleanliness: 9.23", "Service & staff: 8.88", "Room comfort: 9.03",
                      "Hotel condition: 9.05", "Amenities: 8.88", "Eco-friendliness: 8.54"],
  "reviewsExtracted": 50,
  "extractedAt": "2026-07-11T05:31:08Z"
}
```

Ratings are on the **/10 scale** to match Expedia's public display (the source stores /5; we present ×2).

#### Data fields

**Reviews dataset** - one row per review. Every row also carries the hotel context `hotelId`, `hotelName`,
`hotelUrl` and `source` so it stands alone.

| Field | Description |
|---|---|
| `overallRating`, `ratingLabel` | Per-review score (/10) + label ("Exceptional", "Fair"…). |
| `reviewText`, `verified` | Full written review + verified-stay flag. |
| `subRatings` | Per-review category scores (cleanliness, service, amenities…). |
| `submittedAt`, `checkInDate`, `checkOutDate` | Submission + stay dates. |
| `travelCompanions`, `travelerCategories`, `language`, `isMachineTranslated` | Trip context + language. |
| `reviewPhotos`, `helpfulVotes`, `ownerResponse` | Guest photos (URLs), helpful votes, hotel owner reply `{text,date,responder}`. |
| `brandType` | The brand this individual review was posted on (shown as the **Review source** column) - may differ from the hotel-level `source`, which reflects the input URL/ID. |
| `markdownContent` | Self-contained **LLM-ready** markdown block for RAG / vector-DB ingestion. |

**Hotels dataset** - one row per hotel.

| Field | Description |
|---|---|
| `hotelId`, `hotelName`, `hotelUrl`, `source` | Property id (from the URL), name (from the URL slug), source URL, Expedia Group brand. |
| `brandName`, `structureType`, `latitude`, `longitude` | Hotel chain, property type, coordinates. |
| `avgOverallRating`, `halfLifeRating` | Average and recency-weighted rating (**/10**). |
| `totalReviewCount`, `ratingDistribution` | Total reviews available and their source 1-5 star breakdown. |
| `hotelSubRatings`, `categoryCounts`, `languageCounts` | Aggregate category scores (/10), traveler-type counts, per-language counts. |
| `reviewsExtracted`, `extractedAt` | How many reviews this run pulled, and when. |

### Run it via the API

Run the actor programmatically and get the reviews back in one call:

```bash
curl -X POST "https://api.apify.com/v2/acts/factden~expedia-hotel-reviews-scraper/run-sync-get-dataset-items?token=<YOUR_APIFY_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"hotelUrls":["https://www.expedia.com/Las-Vegas-Hotels-Bellagio.h140596.Hotel-Information"],"maxReviewsPerHotel":50}'
```

The response is the default (reviews) dataset - one row per review. Append `?view=aiIngest` for the LLM-ready
markdown columns. The run's **Hotels** dataset (per-hotel aggregate) is available from the run's list of
datasets in the Console or via the API.

### Integrations & export

Download as **JSON, CSV, Excel, or XML**, or push results straight into **Google Sheets, Make, Zapier, n8n, a
webhook**, or your own app via the **Apify API**. AI agents can call this actor through the **Apify MCP server**,
so assistants like **Claude, ChatGPT and LangChain** can pull Expedia reviews on demand. **Schedule** the actor
to run hourly or daily for continuous, incremental review monitoring.

### How much does it cost to scrape Expedia reviews?

This actor uses **pay-per-event** pricing with **no start fee** - you pay only for the reviews you actually get,
and **nothing** if a run returns zero reviews:

| Plan | Price per 1,000 reviews |
|---|---|
| Free | **$2.50** |
| Bronze | **$2.30** |
| Silver | **$2.15** |
| Gold+ | **$2.00** |

**Examples:** 500 reviews ≈ **$1.25** (Free) · 5,000 reviews ≈ **$12.50** (Free) / **$10.00** (Gold). Lower
**Max reviews per hotel** to cap spend, and your first runs are covered by **Apify's free tier**. Unlike many
alternatives, there is **no per-run start fee** - you are never charged just for launching a run.

### Tips & advanced options

- Reviews are fetched **newest-first**, so a tight **From date** plus a low **Max reviews per hotel** is the
  cheapest way to **monitor only what's new** (schedule it daily for incremental review tracking).
- Feed many hotels in one run - the actor **deduplicates** repeated URLs automatically.
- For very large properties (thousands of reviews) the hotel's reviews may be split across a few dataset items to
  keep each item a manageable size; the **Hotels** view still summarizes each property in one row.
- Use **Review sources** to compare the same hotel's reviews across Expedia vs Hotels.com vs Travelocity.

### Related FactDen scrapers

Building a review-intelligence pipeline? Pair this with other FactDen actors on the Apify Store:

- **[G2 Reviews Scraper](https://apify.com/factden/g2-reviews-scraper)** - B2B software reviews, ratings &
  battlecards.
- **[Indeed Jobs Scraper](https://apify.com/factden/indeed-jobs-scraper)** - job listings & company data.
- **[Trip.com & Ctrip Reviews Scraper](https://apify.com/factden/ctrip-trip-reviews-scraper)** - hotel
  reviews across Trip.com / Ctrip.
- **[Google Hotels Scraper](https://apify.com/factden/google-hotels-scraper)** - live hotel prices, the OTA
  rate ladder & guest reviews from Google Hotels.
- **[Hotels.com Reviews Scraper](https://apify.com/factden/hotels-com-reviews-scraper)** - hotel ratings,
- **[MakeMyTrip & Goibibo Reviews Scraper](https://apify.com/factden/makemytrip-scraper)** — MakeMyTrip + Goibibo hotel reviews & details (India's largest OTAs).
  review text & sentiment.
- **[TripAdvisor Hotel Reviews API](https://apify.com/factden/tripadvisor-hotel-reviews-api)** - all TripAdvisor
  reviews for hotels, restaurants & attractions, plus official subratings & the AI review summary.

### FAQ, disclaimers & support

- **Which sites does it support?** All **seven Expedia Group brands** - Expedia, **Hotels.com**, Travelocity,
  Orbitz, Wotif, CheapTickets and ebookers. Paste any brand's hotel URL directly (Hotels.com `/ho<id>/` URLs are
  resolved automatically). Use **Review sources** to pick which brands' reviews to return.
- **Is scraping Expedia reviews legal?** This actor collects only **publicly available** review content and does
  not touch private or account data. You are responsible for complying with Expedia's Terms of Service and
  applicable laws (including data-protection rules like GDPR) when using the data. See Apify's guide,
  [is web scraping legal?](https://blog.apify.com/is-web-scraping-legal/), for background.
- **Do I need an Expedia account or API key?** No.
- **Can I use it via the Apify API or an MCP server?** Yes - run it through the Apify **REST API** (see the
  example above) or connect it to an AI agent via the **Apify MCP server**, so assistants like Claude or ChatGPT
  can fetch Expedia reviews on demand.
- **How many reviews can I get per hotel?** As many as the hotel has - set **Max reviews per hotel** to cap it;
  `totalReviewCount` tells you how many exist in total.
- **How fresh is the data?** Reviews are fetched live and **newest-first**, so you always get the latest ones
  first.
- **Can I get reviews in other languages?** Yes - reviews are returned in their original language with a
  `language` code and an `isMachineTranslated` flag; the hotel aggregate includes per-language counts.
- **A hotel returned fewer reviews than expected.** Your date/rating/source filters, or **Max reviews per
  hotel**, may be limiting the result; `totalReviewCount` shows how many exist in total.
- **Can I schedule it or get only new reviews?** Yes - schedule the actor and set a **From date** to pull only
  reviews since your last run.
- **Found a bug or need a field we don't return?** Open the **Issues** tab on this actor's Apify page.

### Changelog

- **2026-07** - Output split into dedicated **Reviews** and **Hotels** datasets (previously a single dataset
  with views), matching the other FactDen review scrapers.
- **Initial release** - All **7 Expedia Group brands** in one actor; per-review **LLM-ready markdown**;
  incremental **since-date** runs; JSON/CSV/Excel export and full REST API.

***

⭐ **Find this useful?** **Bookmark** the actor and leave a **review** on its Apify Store page - it helps other
travelers and hotel teams find it, and tells us which features to build next.

# Actor input Schema

## `hotelUrls` (type: `array`):

Paste one hotel per line — a hotel page URL from any Expedia Group site (Expedia, Hotels.com, Travelocity, Orbitz, Wotif, CheapTickets, ebookers; any regional domain) or a bare Expedia property ID. Expedia-family URLs carry the id in the `.h<id>.` path; Hotels.com `/ho<id>/` links are resolved automatically. Examples: `https://www.expedia.com/Las-Vegas-Hotels-The-Venetian-Resort-Las-Vegas.h1443.Hotel-Information`, `https://www.hotels.com/ho115902/`, or just `140596`.

## `maxReviewsPerHotel` (type: `integer`):

How many reviews to pull per hotel (fetched newest-first). Lower this to control cost and run time.

## `sortBy` (type: `string`):

Output order of the returned reviews. Reviews are fetched newest-first from the source; `Highest rating` / `Lowest rating` reorder the retrieved set (not a global top-N across the whole hotel).

## `fromDate` (type: `string`):

Keep only reviews submitted on or after this day. Leave empty for no lower bound.

## `toDate` (type: `string`):

Keep only reviews submitted on or before this day. Leave empty for no upper bound.

## `minRating` (type: `integer`):

Keep only reviews with an overall rating at or above this value (1–5).

## `maxRating` (type: `integer`):

Keep only reviews with an overall rating at or below this value (1–5).

## `reviewSources` (type: `array`):

Which Expedia Group brands' reviews to return per hotel. **Leave empty for all brands** (the cross-brand union, e.g. Expedia + Hotels.com reviews for the same property). Pick one for a single-brand filter, or several for a subset.

## `proxyConfiguration` (type: `object`):

Proxy settings. Datacenter proxies are sufficient for Expedia at typical volumes; switch to residential IPs for very large runs.

## Actor input object example

```json
{
  "hotelUrls": [
    "https://www.expedia.com/Las-Vegas-Hotels-The-Venetian-Resort-Las-Vegas.h1443.Hotel-Information",
    "140596",
    "https://www.hotels.com/ho115902/",
    "https://www.travelocity.com/Las-Vegas-Hotels-Caesars-Palace.h41245.Hotel-Information",
    "https://www.orbitz.com/Las-Vegas-Hotels-The-Palazzo.h1769973.Hotel-Information"
  ],
  "maxReviewsPerHotel": 200,
  "sortBy": "newest",
  "minRating": 1,
  "maxRating": 5,
  "reviewSources": [],
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}
```

# Actor output Schema

## `reviews` (type: `string`):

One row per guest review (hotel context merged onto each row) with ratings, full review text, category sub-ratings, stay dates, traveler type, language, owner responses and an LLM-ready markdownContent block.

## `hotels` (type: `string`):

One row per hotel with aggregate average rating, recency-weighted rating, total review count, category sub-ratings, coordinates and how many reviews were extracted.

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "hotelUrls": [
        "https://www.expedia.com/Las-Vegas-Hotels-The-Venetian-Resort-Las-Vegas.h1443.Hotel-Information",
        "140596",
        "https://www.hotels.com/ho115902/",
        "https://www.travelocity.com/Las-Vegas-Hotels-Caesars-Palace.h41245.Hotel-Information",
        "https://www.orbitz.com/Las-Vegas-Hotels-The-Palazzo.h1769973.Hotel-Information"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("factden/expedia-hotel-reviews-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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "hotelUrls": [
        "https://www.expedia.com/Las-Vegas-Hotels-The-Venetian-Resort-Las-Vegas.h1443.Hotel-Information",
        "140596",
        "https://www.hotels.com/ho115902/",
        "https://www.travelocity.com/Las-Vegas-Hotels-Caesars-Palace.h41245.Hotel-Information",
        "https://www.orbitz.com/Las-Vegas-Hotels-The-Palazzo.h1769973.Hotel-Information",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("factden/expedia-hotel-reviews-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 '{
  "hotelUrls": [
    "https://www.expedia.com/Las-Vegas-Hotels-The-Venetian-Resort-Las-Vegas.h1443.Hotel-Information",
    "140596",
    "https://www.hotels.com/ho115902/",
    "https://www.travelocity.com/Las-Vegas-Hotels-Caesars-Palace.h41245.Hotel-Information",
    "https://www.orbitz.com/Las-Vegas-Hotels-The-Palazzo.h1769973.Hotel-Information"
  ]
}' |
apify call factden/expedia-hotel-reviews-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=factden/expedia-hotel-reviews-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/pKHQ6lREbBzmuHAgv/builds/GqWPz7DI4NWbzCcvr/openapi.json