# TripAdvisor Reviews Scraper - $0.40 / 1000 Reviews (`scrapeunblocker/tripadvisor-reviews-scraper`) Actor

Scrape TripAdvisor reviews of hotels, restaurants and attractions: title, full text, rating, sub-ratings, dates, trip type, language, reviewer profile, photos and the owner's response, with the place's rating and details on every row. Any TripAdvisor site, date filter. $0.40 per 1000 reviews.

- **URL**: https://apify.com/scrapeunblocker/tripadvisor-reviews-scraper.md
- **Developed by:** [Scrapeunblocker](https://apify.com/scrapeunblocker) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.40 / 1,000 reviews

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## TripAdvisor Reviews Scraper

Scrape **TripAdvisor reviews** of hotels, restaurants and attractions as clean structured JSON - review title and full text, rating and sub-ratings, publish and travel dates, trip type, language, reviewer profile, photos and the **owner's response** - with the place's name, rating and URL on every row. No login, no proxies or browsers to configure.

Works with review pages on any TripAdvisor site (tripadvisor.com, .co.uk, .de, .fr, .it, .es, ...) and with bare location IDs.

### Features

- **Hotels, restaurants and attractions** - `Hotel_Review`, `Restaurant_Review`, `Attraction_Review` and `AttractionProductReview` pages.
- **Full review data** - title, text, rating, sub-ratings (value, rooms, location, cleanliness, service, sleep quality), published date, travel date, trip type, helpful votes, photos.
- **Reviewer profile** - name, username, location, contributions, profile URL, avatar.
- **Owner responses** - text, date, author and role.
- **Deep history** - collect thousands of reviews per place; paging is handled for you.
- **Language filter** - 13 languages; reviews in other languages are flagged when machine-translated.
- **Date filter** - only reviews published since a given date, ideal for incremental monitoring.
- **Place details** - the full place record (rating histogram, review counts by language, ranking, address, coordinates, phone, website) is saved in the key-value store as a `PLACE-<id>` record.

### Use cases

- Reputation monitoring for hotels, restaurants and tour operators.
- Sentiment and topic analysis across competitors.
- Tracking response rates and owner replies.
- Weekly incremental review exports with the `since` filter.

### Input

| Field | Type | Default | Description |
|-------|------|---------|-------------|
| `places` | array | The Michelangelo New York | Review page URLs or location IDs. |
| `max_reviews_per_place` | integer | `20` | Reviews to collect per place (newest first). |
| `language` | string | `auto` | Review language (`en`, `de`, `fr`, `it`, `es`, `pt`, `nl`, `ja`, `ko`, `ru`, `sv`, `tr`, `da`). |
| `since` | string | - | Only reviews published on or after this date (YYYY-MM-DD). |
| `concurrency` | integer | `1` | Places scraped at the same time (1-2). |

#### Example input

```json
{
  "places": [
    "https://www.tripadvisor.com/Hotel_Review-g60763-d93589-Reviews-The_Michelangelo_New_York-New_York_City_New_York.html",
    "https://www.tripadvisor.co.uk/Restaurant_Review-g186338-d3896790-Reviews-Balthazar-London_England.html"
  ],
  "max_reviews_per_place": 100,
  "since": "2026-01-01"
}
```

### Output

One dataset item per review:

```json
{
  "placeName": "The Michelangelo New York",
  "placeLocationId": 93589,
  "placeUrl": "https://www.tripadvisor.com/Hotel_Review-g60763-d93589-Reviews-The_Michelangelo_New_York-New_York_City_New_York.html",
  "placeType": "hotel",
  "placeRating": 4.5,
  "placeReviewsCount": 5213,
  "placeCity": "New York City",
  "placeCountry": "US",
  "id": 1078193437,
  "url": "https://www.tripadvisor.com/ShowUserReviews-g60763-d93589-r1078193437-...",
  "title": "Consistent Excellence and Value in NYC!",
  "text": "My partner and I have been happily staying at the Michelangelo for over 30 years...",
  "rating": 5,
  "publishedDate": "2026-09-17",
  "travelDate": "2026-05",
  "tripType": "couples",
  "language": "en",
  "isMachineTranslated": false,
  "helpfulVotes": 0,
  "user": { "name": "Peter F", "location": "Toronto, Canada", "contributions": 11 },
  "subratings": { "value": 5, "rooms": 5, "location": 5, "cleanliness": 5, "service": 5 },
  "photos": [],
  "ownerResponse": { "text": "After more than 30 years of visits...", "publishedDate": "2026-09-19", "author": "Hotel Manager" }
}
```

Places that return no reviews (wrong URL, no reviews in the chosen language or after the `since` date) are listed in the `ERRORS` record of the key-value store and are **not billed**.

### Pricing

**$0.40 per 1000 reviews.** You pay only for reviews delivered; failed places are not charged.

### Notes

- Each page of reviews is rendered in a real browser, so expect roughly 5-30 seconds per 10-20 reviews.
- TripAdvisor ties review languages to its regional sites; `auto` uses the language of the URL's site.

# Actor input Schema

## `places` (type: `array`):

TripAdvisor review page URLs of hotels (Hotel\_Review), restaurants (Restaurant\_Review) or attractions (Attraction\_Review, AttractionProductReview) on any TripAdvisor site, or bare location IDs (the digits after -d in the URL, e.g. 93589).

## `max_reviews_per_place` (type: `integer`):

How many reviews to collect for each place, newest first. TripAdvisor shows 10 reviews per page (15 for restaurants), so large numbers take a few minutes per place.

## `language` (type: `string`):

Which language's reviews to collect. Reviews written in other languages may come back machine-translated (flagged by isMachineTranslated).

## `since` (type: `string`):

Optional. Only reviews published on or after this date (YYYY-MM-DD). Paging stops as soon as older reviews start, so it also makes runs faster.

## `proxy_country` (type: `string`):

ISO-2 country to browse TripAdvisor from. Leave empty: a pinned country cannot use the fast pre-warmed browsers and is much slower.

## `concurrency` (type: `integer`):

How many places to scrape at the same time (1-2).

## Actor input object example

```json
{
  "places": [
    "https://www.tripadvisor.com/Hotel_Review-g60763-d93589-Reviews-The_Michelangelo_New_York-New_York_City_New_York.html"
  ],
  "max_reviews_per_place": 20,
  "language": "auto",
  "proxy_country": "",
  "concurrency": 1
}
```

# Actor output Schema

## `results` (type: `string`):

One item per review, with the place's name, rating and URL

## `errors` (type: `string`):

Places that returned no reviews, with the reason (not billed)

# 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 = {
    "places": [
        "https://www.tripadvisor.com/Hotel_Review-g60763-d93589-Reviews-The_Michelangelo_New_York-New_York_City_New_York.html"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("scrapeunblocker/tripadvisor-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 = { "places": ["https://www.tripadvisor.com/Hotel_Review-g60763-d93589-Reviews-The_Michelangelo_New_York-New_York_City_New_York.html"] }

# Run the Actor and wait for it to finish
run = client.actor("scrapeunblocker/tripadvisor-reviews-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "places": [
    "https://www.tripadvisor.com/Hotel_Review-g60763-d93589-Reviews-The_Michelangelo_New_York-New_York_City_New_York.html"
  ]
}' |
apify call scrapeunblocker/tripadvisor-reviews-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,scrapeunblocker/tripadvisor-reviews-scraper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/43gKY6sCllxImCuKN/builds/ArIEJLTg0fh3Jxcf0/openapi.json