# Tripadvisor Reviews Scraper (`fetch_cat/tripadvisor-reviews-scraper`) Actor

Export public Tripadvisor reviews with ratings, reviewer details, owner responses, photos, filters, and reliable pagination.

- **URL**: https://apify.com/fetch\_cat/tripadvisor-reviews-scraper.md
- **Developed by:** [Hanna Nosova](https://apify.com/fetch_cat) (community)
- **Categories:** Travel, Marketing, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.02 / 1,000 review saveds

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

## Tripadvisor Reviews Scraper

Export public Tripadvisor hotel, restaurant, and attraction reviews to a structured dataset. Collect review text and ratings together with reviewer details, management responses, photos, subratings, place metadata, and source provenance.

Use the results for guest-feedback analysis, reputation monitoring, hospitality research, review aggregation, and BI or AI pipelines. Teams can **scrape Tripadvisor reviews** through the web interface or use the **Tripadvisor reviews API** workflow through Apify. Supply one or more Tripadvisor place URLs; the Actor handles pagination, duplicate removal, filtering, and partial multi-URL failures.

### Example input

```json
{
  "startUrls": [
    { "url": "https://www.tripadvisor.com/Hotel_Review-g60763-d208453-Reviews-Hilton_New_York_Times_Square-New_York_City_New_York.html" }
  ],
  "maxReviewsPerUrl": 20,
  "sort": "recent",
  "ratings": [4, 5],
  "languages": ["en"]
}
```

### Example output

```json
{
  "reviewId": "1072075477",
  "reviewUrl": "https://www.tripadvisor.com/ShowUserReviews-g60763-d208453-r1072075477.html",
  "title": "2 Nights In Times Square",
  "text": "My family and I spent two nights at this hotel...",
  "rating": 4,
  "publishedDate": "2026-08-07",
  "travelDate": "2026-08-31",
  "helpfulVotes": 0,
  "language": "en",
  "userId": "62BA843EB814DC878D7A6BB6ED490AAD",
  "username": "DFunk",
  "userProfileUrl": "https://www.tripadvisor.com/Profile/DRDFunk",
  "userAvatarUrl": null,
  "userLocation": "New York",
  "userContributions": 1,
  "ownerResponse": { "id": "1072517231", "text": "Thank you...", "publishedDate": "2026-08-10" },
  "photos": [],
  "subratings": {},
  "placeId": "208453",
  "placeName": "Hilton New York Times Square",
  "placeUrl": "https://www.tripadvisor.com/Hotel_Review-g60763-d208453-Reviews-Hilton_New_York_Times_Square-New_York_City_New_York.html",
  "placeRating": 4.5,
  "placeReviewCount": 9500,
  "placeAddress": "234 W 42nd St, New York City, NY",
  "sourceUrl": "https://www.tripadvisor.com/Hotel_Review-g60763-d208453-Reviews-Hilton_New_York_Times_Square-New_York_City_New_York.html",
  "scrapedAt": "2026-08-13T11:56:17.403Z"
}
```

### What data can you export?

| Field | Description |
|---|---|
| `reviewId` | Tripadvisor review identifier |
| `reviewUrl` | Direct public review URL |
| `title` | Review title |
| `text` | Full review text |
| `rating` | Overall rating from 1 to 5 |
| `publishedDate` | Review publication date |
| `travelDate` | Visit or stay date when available |
| `helpfulVotes` | Helpful-vote count |
| `language` | Review language code |
| `userId` | Public reviewer identifier |
| `username` | Public reviewer display name |
| `userProfileUrl` | Reviewer profile URL |
| `userAvatarUrl` | Reviewer avatar URL |
| `userLocation` | Public reviewer location |
| `userContributions` | Public contribution count |
| `ownerResponse` | Management-response ID, text, and date |
| `photos` | Review photo IDs, image URLs, and captions |
| `subratings` | Category-level ratings where available |
| `placeId` | Tripadvisor place identifier |
| `placeName` | Hotel, restaurant, or attraction name |
| `placeUrl` | Canonical place URL |
| `placeRating` | Overall place rating |
| `placeReviewCount` | Total public review count |
| `placeAddress` | Public place address |
| `sourceUrl` | Input URL that produced the review |
| `scrapedAt` | UTC extraction timestamp |

Optional fields are returned as `null`, `{}`, or `[]` when Tripadvisor does not publish them for a review.

### Input settings

| Input | Type | Default | Description |
|---|---|---:|---|
| `startUrls` | array | required | 1–20 Tripadvisor hotel, restaurant, or attraction URLs |
| `maxReviewsPerUrl` | integer | `20` | Maximum reviews saved for each URL (1–500) |
| `startPage` | integer | `0` | Zero-based page to start from for resume workflows |
| `sort` | string | `recent` | Sort reviews by `recent` or `relevant` |
| `ratings` | integer\[] | all | Keep ratings from 1 to 5 |
| `languages` | string\[] | all | Keep language codes such as `en`, `de`, or `pt-BR` |
| `dateFrom` | string | none | Earliest publication date (`YYYY-MM-DD`) |
| `dateTo` | string | none | Latest publication date (`YYYY-MM-DD`) |
| `failOnError` | boolean | `false` | Stop on the first failed URL instead of preserving partial results |

### Ready-to-run examples

Open a public example to inspect its input, run it, or reuse it as a task:

- [Export Five-Star Tripadvisor Reviews](https://apify.com/fetch_cat/tripadvisor-reviews-scraper/examples/export-five-star-tripadvisor-reviews)
- [Export Latest Tripadvisor Hotel Reviews](https://apify.com/fetch_cat/tripadvisor-reviews-scraper/examples/export-latest-tripadvisor-hotel-reviews)

**Latest reviews for several properties**

```json
{"startUrls":[{"url":"https://www.tripadvisor.com/Hotel_Review-g60763-d208453-Reviews-Hilton_New_York_Times_Square-New_York_City_New_York.html"}],"maxReviewsPerUrl":100,"sort":"recent"}
```

**Recent English five-star reviews**

```json
{"startUrls":[{"url":"https://www.tripadvisor.com/Hotel_Review-g60763-d208453-Reviews-Hilton_New_York_Times_Square-New_York_City_New_York.html"}],"maxReviewsPerUrl":50,"ratings":[5],"languages":["en"],"dateFrom":"2026-01-01"}
```

### Who is it for?

- **Hospitality operators** monitoring guest sentiment and management-response coverage.
- **Agencies and analysts** comparing customer experience across many properties.
- **Researchers and data teams** building review datasets for BI, NLP, or AI workflows.
- **Developers and automation teams** integrating Tripadvisor review data into applications.

### Use cases

- Monitor guest sentiment and management-response coverage.
- Compare customer experience across hotels, restaurants, or attractions.
- Feed review text into topic, sentiment, or LLM analysis.
- Build recurring dashboards in Google Sheets, Airtable, databases, or BI tools.
- Archive public reviews with deterministic source provenance.

### Pricing

The Actor uses pay-per-event pricing with a small run-start charge and a per-review charge. Higher-volume plans receive tiered discounts. You pay only for dataset items saved; failed or filtered rows are not charged as review results. See the [live Pricing tab](https://apify.com/fetch_cat/tripadvisor-reviews-scraper/pricing) for current rates.

### API usage

```bash
curl -X POST "https://api.apify.com/v2/acts/fetch_cat~tripadvisor-reviews-scraper/runs?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"startUrls":[{"url":"https://www.tripadvisor.com/Hotel_Review-g60763-d208453-Reviews-Hilton_New_York_Times_Square-New_York_City_New_York.html"}],"maxReviewsPerUrl":20}'
```

**JavaScript**

```javascript
import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('fetch_cat/tripadvisor-reviews-scraper').call({
  startUrls: [{ url: 'https://www.tripadvisor.com/Hotel_Review-g60763-d208453-Reviews-Hilton_New_York_Times_Square-New_York_City_New_York.html' }],
  maxReviewsPerUrl: 20,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);
```

**Python**

```python
import os
from apify_client import ApifyClient

client = ApifyClient(os.environ['APIFY_TOKEN'])
run = client.actor('fetch_cat/tripadvisor-reviews-scraper').call(run_input={
    'startUrls': [{'url': 'https://www.tripadvisor.com/Hotel_Review-g60763-d208453-Reviews-Hilton_New_York_Times_Square-New_York_City_New_York.html'}],
    'maxReviewsPerUrl': 20,
})
items = client.dataset(run['defaultDatasetId']).list_items().items
print(items)
```

The run's default dataset can be exported as JSON, CSV, Excel, XML, or RSS. Use Apify integrations to send results to Google Sheets, Make, Zapier, webhooks, or your own application.

### MCP and AI agents

Connect the Actor to an MCP-compatible client through `https://mcp.apify.com/?tools=fetch_cat/tripadvisor-reviews-scraper`.

**Claude Code CLI**

```bash
claude mcp add apify --transport http "https://mcp.apify.com/?tools=fetch_cat/tripadvisor-reviews-scraper"
```

**MCP JSON configuration**

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

Example prompts:

- “Export the 50 latest English reviews for this Tripadvisor hotel and summarize recurring complaints.”
- “Run the Tripadvisor Reviews Scraper for these property URLs and return a CSV-ready dataset.”

Your agent can start review exports, inspect run status, and consume structured datasets without custom scraping code.

### Limits and reliability

- Public Tripadvisor place URLs only; search pages and private/account data are unsupported.
- A run accepts up to 20 URLs and 500 reviews per URL.
- Date and language availability follows the public review data.
- Output is saved progressively. If one URL fails, successful URLs remain available unless `failOnError` is enabled.
- Source changes, rate limits, or temporary anti-bot challenges can cause partial runs; retry failed sources later.
- Respect Tripadvisor's terms, applicable privacy rules, and local law. Do not use the Actor to profile individuals or collect sensitive data.

### Tips

- Start with 20 reviews and increase the limit after checking the output.
- Use `sourceUrl` to group results from batch runs.
- Combine `startPage` with a fixed sort order for controlled continuation.
- Leave `ratings` and `languages` empty to avoid filtering out valid reviews.

### FAQ

#### Does it work for hotels, restaurants, and attractions?

Yes. Provide a public Tripadvisor detail page containing a place ID in its URL.

#### Is there an API for Tripadvisor hotel reviews?

Yes. Run this Actor as a Tripadvisor reviews API using the Apify API, JavaScript/Python clients, CLI, webhooks, or MCP.

#### How can I export Tripadvisor reviews to CSV or JSON?

Run the Actor, then download its default dataset as CSV, JSON, Excel, XML, or RSS. It exports repeatable structured data with pagination, filtering, and deduplication.

#### Why are some fields empty?

Travel dates, photos, subratings, reviewer location, and owner responses are optional and are not published on every review.

#### Can I request more than the platform limit?

The current limit is 500 reviews per URL and 20 URLs per run. Split larger jobs into multiple runs using `startPage`.

#### Is scraping public reviews legal?

Laws vary. Only public data is collected, but you are responsible for your use case, Tripadvisor's terms, and applicable privacy and database rules.

### Related Actors

- [Google Maps Scraper](https://apify.com/fetch_cat/google-maps-scraper)
- [Google Maps Reviews Scraper](https://apify.com/fetch_cat/google-maps-reviews-scraper)
- [Trustpilot Scraper](https://apify.com/fetch_cat/trustpilot-scraper)
- [Booking Scraper](https://apify.com/fetch_cat/booking-scraper)
- [Yelp Scraper](https://apify.com/fetch_cat/yelp-scraper)

### Support

If a valid public Tripadvisor URL fails or the output shape changes, open an issue from the Actor page and include the run URL and a non-sensitive example input. We maintain the Actor as Tripadvisor evolves.

# Actor input Schema

## `startUrls` (type: `array`):

Add 1–20 public hotel, restaurant, or attraction URLs. Each URL must contain a -d location ID.

## `maxReviewsPerUrl` (type: `integer`):

Maximum reviews saved for each place URL.

## `startPage` (type: `integer`):

Zero-based review page used to resume a previous export.

## `sort` (type: `string`):

Request recent or Tripadvisor-relevant review order.

## `ratings` (type: `array`):

Optional JSON array of star ratings to include, for example \[4, 5].

## `languages` (type: `array`):

Optional review language codes, for example en, de, or fr.

## `dateFrom` (type: `string`):

Only save reviews published on or after this date (YYYY-MM-DD).

## `dateTo` (type: `string`):

Only save reviews published on or before this date (YYYY-MM-DD).

## `failOnError` (type: `boolean`):

Stop the run when one source fails. Leave disabled to preserve reviews from successful URLs and report partial failures.

## Actor input object example

```json
{
  "startUrls": [
    {
      "url": "https://www.tripadvisor.com/Hotel_Review-g60763-d208453-Reviews-Hilton_New_York_Times_Square-New_York_City_New_York.html"
    }
  ],
  "maxReviewsPerUrl": 20,
  "startPage": 0,
  "sort": "recent",
  "failOnError": false
}
```

# Actor output Schema

## `overview` (type: `string`):

No description

# 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 = {
    "startUrls": [
        {
            "url": "https://www.tripadvisor.com/Hotel_Review-g60763-d208453-Reviews-Hilton_New_York_Times_Square-New_York_City_New_York.html"
        }
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("fetch_cat/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 = { "startUrls": [{ "url": "https://www.tripadvisor.com/Hotel_Review-g60763-d208453-Reviews-Hilton_New_York_Times_Square-New_York_City_New_York.html" }] }

# Run the Actor and wait for it to finish
run = client.actor("fetch_cat/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 '{
  "startUrls": [
    {
      "url": "https://www.tripadvisor.com/Hotel_Review-g60763-d208453-Reviews-Hilton_New_York_Times_Square-New_York_City_New_York.html"
    }
  ]
}' |
apify call fetch_cat/tripadvisor-reviews-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,fetch_cat/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/xxl42PjKtUj34DWuH/builds/vorEzr5vzd8z2cB4s/openapi.json