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

{
  "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

{
  "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?

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

Input settings

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.

API usage

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

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

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

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

MCP JSON configuration

{
  "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.

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.