# Tripadvisor Review Scraper (`louvre/tripadvisor-review-scraper`) Actor

The Tripadvisor Review Scraper is a powerful and easy-to-use actor designed to collect structured review data from Tripadvisor product pages. Whether you’re analyzing customer sentiment, monitoring competitor feedback, or enriching your travel content.

- **URL**: https://apify.com/louvre/tripadvisor-review-scraper.md
- **Developed by:** [Louvre LLC](https://apify.com/louvre) (community)
- **Categories:** Travel, AI, Agents
- **Stats:** 38 total users, 2 monthly users, 99.9% runs succeeded, 3 bookmarks
- **User rating**: No ratings yet

## Pricing

from $3.00 / 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.

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 Review Scraper

### 📌 Introduction

Tripadvisor Review Scraper is a powerful and easy-to-use **Apify Actor** designed to collect structured **review data** from Tripadvisor product pages. Whether you're analyzing customer sentiment, monitoring traveler feedback, or enriching your travel content, this Actor helps you extract data at scale — pricing is pay-per-result.

***

### 💡 Free vs paid plans

On a free Apify plan, this actor returns a **sample** of the reviews. Upgrade to any paid Apify plan to get the **complete** results.

***

### 🎯 What is this Review Scraper?

This Actor automatically scrapes reviews from a given **Tripadvisor product URL** and produces structured dataset output that you can download or integrate via API. It's perfect for travel market research, competitive analysis, sentiment tracking, and more.

***

### 🔍 Features

- ⭐ **Structured Review Data** — Extract ratings, review text, reviewer info, photos, dates, and more.
- 🔁 **Flexible Pagination** — Easily scrape multiple pages of reviews.
- 🚀 **Efficient Extraction** — Designed to handle a large number of reviews.
- 🧹 **Clean Output** — Produces organized dataset entries ready for analysis.
- 🔌 **Easy Integration** — Use with Apify API or workflow automation tools.

***

### 🧰 Input Parameters

| Parameter      | Type          | Required | Description |
|----------------|---------------|----------|-------------|
| `product_url`  | String        | ⚠️       | The Tripadvisor product page URL to scrape reviews from. Either `product_url` or `product_urls` must be provided. |
| `product_urls` | Array\[String] | ⚠️       | Array of Tripadvisor product URLs for batch processing. Either `product_url` or `product_urls` must be provided. |
| `page_size`    | Number        | ❌       | Maximum number of reviews per page (default: 100). |
| `page`         | Number        | ❌       | Start page number; will skip (page – 1) \* page_size reviews from the beginning (default: 1). |

***

### 📥 Example Input

#### Single URL

```json
{
  "product_url": "https://www.tripadvisor.com/AttractionProductReview-g187791-d12268171-Rome_Skip_the_Line_Vatican_Sistine_Chapel_St_Peter_Small_Group-Rome_Lazio.html",
  "page_size": 100,
  "page": 1
}
```

#### Batch Processing (Multiple URLs)

```json
{
  "product_urls": [
    "https://www.tripadvisor.com/AttractionProductReview-g187791-d12268171-Rome_Skip_the_Line_Vatican_Sistine_Chapel_St_Peter_Small_Group-Rome_Lazio.html",
    "https://www.tripadvisor.com/AttractionProductReview-g187791-d11480167-Vatican_Museums_Sistine_Chapel_Tour_and_Basilica_Access-Rome_Lazio.html"
  ],
  "page_size": 100,
  "page": 1
}
```

This configuration will scrape up to 100 reviews starting from the first page of the specified Tripadvisor product(s).

***

### 🗃️ Output Data

Each review returned by this Actor includes the following structured fields:

| Field                    | Type     | Description |
|--------------------------|----------|-------------|
| `id`                     | String   | Unique review identifier. |
| `review_id`              | String   | Original Tripadvisor review ID. |
| `product_id`             | String   | Tripadvisor product identifier. |
| `rating`                 | String   | Review rating, 1–5 stars, returned as a string (e.g. "5.00"). |
| `title`                  | String   | Review title. |
| `content`                | String   | Full review text. |
| `author_name`            | String   | Reviewer's name. |
| `user_identifier_value`  | String   | Author user identifier. |
| `review_date`            | String   | Date when the review was published (ISO 8601 format). |
| `trip_type`              | String   | Type of travel (solo, couple, family, etc.). |
| `helpful_votes`          | Number   | Number of helpful votes. |
| `photos`                 | Array    | Array of photo URLs (if any). |
| `owner_response`         | String   | Business owner response text (if any). |
| `owner_response_author`  | String   | Response author name (if any). |
| `owner_response_date`    | String   | Response publication date (ISO 8601 format, if any). |
| `language`               | String   | Review language code. |
| `overall_star_rating`    | Number   | Overall product star rating (e.g. 4.5 out of 5). `-1` if unavailable. |
| `overall_review_count`   | Number   | Total number of reviews for the product. `-1` if unavailable. |

***

### 🧠 How It Works

1. **Input Acceptance** — Takes a list of Tripadvisor page URLs from the user.
2. **Web Scraping** — Visits each URL and parses visible review data from the page DOM.
3. **Data Structuring** — Normalizes extracted fields into structured records.
4. **Dataset Storage** — Saves results in the Apify dataset for retrieval via UI or API.

***

### ⚙️ Usage Examples

#### 📦 Basic Usage

```json
{
  "product_url": "https://www.tripadvisor.com/AttractionProductReview-g187791-d12268171-Rome_Skip_the_Line_Vatican_Sistine_Chapel_St_Peter_Small_Group-Rome_Lazio.html"
}
```

#### 📈 With Pagination

```json
{
  "product_url": "https://www.tripadvisor.com/AttractionProductReview-g187791-d12268171-Rome_Skip_the_Line_Vatican_Sistine_Chapel_St_Peter_Small_Group-Rome_Lazio.html",
  "page_size": 200,
  "page": 2
}
```

Attempts to extract up to 200 reviews from the specified Tripadvisor product page.

#### 🔄 Batch Processing (Multiple URLs)

```json
{
  "product_urls": [
    "https://www.tripadvisor.com/AttractionProductReview-g187791-d12268171-Rome_Skip_the_Line_Vatican_Sistine_Chapel_St_Peter_Small_Group-Rome_Lazio.html",
    "https://www.tripadvisor.com/AttractionProductReview-g187791-d11480167-Vatican_Museums_Sistine_Chapel_Tour_and_Basilica_Access-Rome_Lazio.html",
    "https://www.tripadvisor.com/AttractionProductReview-g187791-d18909282-Rome_Colosseum_Guided_Tour_with_Roman_Forum_and_Palatine_Hill-Rome_Lazio.html"
  ],
  "page_size": 100,
  "page": 1
}
```

***

### 🤖 Use Tripadvisor Review Scraper in Claude, Cursor & Codex via MCP

You can call this Actor directly from an AI assistant through the [Apify MCP server](https://mcp.apify.com) — it works with **Claude**, **Cursor**, **Codex**, and any other MCP client.

Add this connector URL in your MCP client:

```
https://mcp.apify.com/?tools=louvre/tripadvisor-review-scraper
```

Then ask in plain language, for example:

> "Get the latest reviews for this Tripadvisor page: https://www.tripadvisor.com/AttractionProductReview-g187791-d12268171-Rome_Skip_the_Line_Vatican_Sistine_Chapel_St_Peter_Small_Group-Rome_Lazio.html"

For a ready-to-paste configuration (Claude Desktop, Cursor, VS Code, and more), open the **API → MCP** tab on this Actor's page.

***

### 📡 API / CLI Integration

You can run this Actor programmatically via the Apify API. Example (curl):

```bash
curl "https://api.apify.com/v2/acts/louvre~tripadvisor-review-scraper/runs?token=<YOUR_API_TOKEN>" \
  -X POST \
  -H "Content-Type: application/json" \
  -d @input.json
```

Replace `<YOUR_API_TOKEN>` with your Apify token and `input.json` with your JSON input.

***

### 💰 Pricing & Limits

This Actor uses **pay-per-result** pricing — see the **Pricing** tab on the Actor page for the current rate. A free trial is available.

***

### 🔗 Related Links

- 🌐 Actor page: https://apify.com/louvre/tripadvisor-review-scraper
- 📜 API docs: https://apify.com/louvre/tripadvisor-review-scraper/api

# Changelog

This Actor's version history is a separate document: https://apify.com/louvre/tripadvisor-review-scraper/changelog.md

# Actor input Schema

## `product_url` (type: `string`):

The TripAdvisor product URL to scrape reviews from

## `product_urls` (type: `array`):

Array of TripAdvisor product URLs to scrape reviews from. Use this field for batch processing multiple URLs. Format: \["url1", "url2", ...]. Leave empty if using product_url field instead.

## `page_size` (type: `integer`):

Maximum number of reviews for every page (default: 100)

## `page` (type: `integer`):

Start page number, will skip (page - 1) \* pageSize from the beginning (default: 1)

## Actor input object example

```json
{
  "product_url": "https://www.tripadvisor.com/AttractionProductReview-g187791-d12268171-Rome_Skip_the_Line_Vatican_Sistine_Chapel_St_Peter_Small_Group-Rome_Lazio.html",
  "page_size": 100,
  "page": 1
}
```

# Actor output Schema

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

All scraped Tripadvisor reviews stored in the default dataset

# 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 = {
    "product_url": "https://www.tripadvisor.com/AttractionProductReview-g187791-d12268171-Rome_Skip_the_Line_Vatican_Sistine_Chapel_St_Peter_Small_Group-Rome_Lazio.html",
    "page_size": 100,
    "page": 1
};

// Run the Actor and wait for it to finish
const run = await client.actor("louvre/tripadvisor-review-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 = {
    "product_url": "https://www.tripadvisor.com/AttractionProductReview-g187791-d12268171-Rome_Skip_the_Line_Vatican_Sistine_Chapel_St_Peter_Small_Group-Rome_Lazio.html",
    "page_size": 100,
    "page": 1,
}

# Run the Actor and wait for it to finish
run = client.actor("louvre/tripadvisor-review-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 '{
  "product_url": "https://www.tripadvisor.com/AttractionProductReview-g187791-d12268171-Rome_Skip_the_Line_Vatican_Sistine_Chapel_St_Peter_Small_Group-Rome_Lazio.html",
  "page_size": 100,
  "page": 1
}' |
apify call louvre/tripadvisor-review-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,louvre/tripadvisor-review-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/Q9AcyUWWAa60hZZ36/builds/xYm6bJ0JmcTHiIgxq/openapi.json