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Tripadvisor Reviews Scraper

Give it Tripadvisor hotel, restaurant or attraction pages (or place names) and it returns one JSON row per review: rating, title, original-language text with an optional translation, date, sub-ratings, trip type, the owner reply with its date, and the place's overall rating and review count. $4.50 per 1,000 reviews on the free plan, less on paid plans; you pay only for rows you get.

$4.50 per 1,000 reviews on the Free plan, down to $0.80 on higher plans

Why this actor

Drop-in input

Easy switch. The input names of the most used Tripadvisor reviews actor are accepted as they are.

As stated in the actor’s README. The full list of accepted input names is on the Store page.

What you get

FieldWhat it holds
reviewIdTripadvisor___ plus the platform's own review ID. Stable between runs, so you can dedupe weekly exports.
dateDate the review was written, ISO format.
title, textWhat the reviewer wrote, in the language it was written in.
extras.translatedTitle, extras.translatedText, extras.translatedLanguageMachine translation of a review written in another language, next to the original. Only with translateTo.
extras.originalLanguageLanguage the review was written in.
product.rating, product.reviewCountrating is the average of all review ratings of the place (computed from its star histogram, not Tripadvisor's rounded bubble rating); reviewCount is the total number of reviews. Repeated on every row. Turn off with includePlaceSummary.
ratingOverallOverall bubble rating, 1 to 5.
ratingsSub-ratings the reviewer filled in (value, rooms, location, cleanliness, service, sleep quality). Skipped ones are left out.
vendorResponse, extras.ownerResponseDateThe owner or manager reply and the date it was posted, when there is one.
helpfulVotes, language, reviewerVerifiedHelpful votes, review language, and whether the review is marked as verified.
productName, productUrl, reviewUrlThe place and where the review lives.
extras.tripTypeBusiness, couples, family, friends or solo.
extras.visitDateMonth of the visit (yyyy-mm).
extras.photoUrlsPhotos attached to the review.
extras.totalCountHow many reviews match your filters at that place.
scrapedAtWhen the row was collected.

Sample row (from the README example; long text shortened, lists cut to two items):

{
  "reviewId": "Tripadvisor___123456789",
  "platform": "tripadvisor",
  "productName": "Example Grand Hotel",
  "date": "2026-09-27",
  "title": "Great stay",
  "text": "Quiet room, friendly staff.",
  "ratingOverall": 5,
  "ratings": {
    "value": 5,
    "cleanliness": 5
  },
  "language": "en",
  "vendorResponse": "Dear [name], thank you for staying with us.",
  "extras": {
    "tripType": "COUPLES",
    "visitDate": "2026-08",
    "placeType": "ACCOMMODATION"
  }
}

Price

Live Apify price on 2026-10-31, per 1,000 rows, by Apify plan. You pay only for rows delivered; error and summary rows marked free in the README cost nothing. Plus $0.001 per GB of memory when a run starts.

Per 1,000FreeBronzeSilverGoldPlatinumDiamond
Review (main)$4.50$1.75$1.35$0.80$0.80$0.80

Use cases

Run it from code or an AI agent

Actor ID arcadium/tripadvisor-reviews. Set APIFY_TOKEN to your Apify API token. The input below is the actor’s prefilled example; see the guide for every field.

curl
curl -X POST "https://api.apify.com/v2/acts/arcadium~tripadvisor-reviews/run-sync-get-dataset-items" \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"startUrls":[{"url":"https://www.tripadvisor.com/Hotel_Review-g60763-d93450-Reviews-Hyatt_Grand_Central_New_York-New_York_City_New_York.html"}],"maxReviewsPerPlace":20}'
JavaScript
// npm install apify-client
import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('arcadium/tripadvisor-reviews').call({
  "startUrls": [
    {
      "url": "https://www.tripadvisor.com/Hotel_Review-g60763-d93450-Reviews-Hyatt_Grand_Central_New_York-New_York_City_New_York.html"
    }
  ],
  "maxReviewsPerPlace": 20
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);
Python
# pip install apify-client
import os
from apify_client import ApifyClient

client = ApifyClient(os.environ["APIFY_TOKEN"])
run = client.actor("arcadium/tripadvisor-reviews").call(run_input={
    "startUrls": [{
        "url": "https://www.tripadvisor.com/Hotel_Review-g60763-d93450-Reviews-Hyatt_Grand_Central_New_York-New_York_City_New_York.html",
    }],
    "maxReviewsPerPlace": 20,
})
items = client.dataset(run["defaultDatasetId"]).list_items().items
print(items)
MCP
{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com/?tools=arcadium/tripadvisor-reviews",
      "headers": {
        "Authorization": "Bearer <APIFY_TOKEN>"
      }
    }
  }
}
LangChain
# pip install langchain-apify   (reads APIFY_API_TOKEN from the environment)
from langchain_apify import ApifyActorsTool

tool = ApifyActorsTool("arcadium/tripadvisor-reviews")
rows = tool.invoke({"run_input": {
    "startUrls": [{
        "url": "https://www.tripadvisor.com/Hotel_Review-g60763-d93450-Reviews-Hyatt_Grand_Central_New_York-New_York_City_New_York.html",
    }],
    "maxReviewsPerPlace": 20,
}})
# or give `tool` to an agent: create_react_agent(llm, [tool])
LlamaIndex
# pip install llama-index-readers-apify
import os
from llama_index.core import Document, VectorStoreIndex
from llama_index.readers.apify import ApifyActor

reader = ApifyActor(os.environ["APIFY_TOKEN"])
documents = reader.load_data(
    actor_id="arcadium/tripadvisor-reviews",
    run_input={
        "startUrls": [{
            "url": "https://www.tripadvisor.com/Hotel_Review-g60763-d93450-Reviews-Hyatt_Grand_Central_New_York-New_York_City_New_York.html",
        }],
        "maxReviewsPerPlace": 20,
    },
    dataset_mapping_function=lambda item: Document(text=str(item.get("text") or ""), metadata={"url": item.get("url")}),
)
index = VectorStoreIndex.from_documents(documents)
CrewAI
# pip install crewai crewai-tools langchain-apify   (reads APIFY_API_TOKEN from the environment)
from crewai import Agent
from crewai_tools import ApifyActorsTool

tool = ApifyActorsTool(actor_name="arcadium/tripadvisor-reviews")
researcher = Agent(
    role="Research analyst",
    goal="Answer with data collected by the tool",
    backstory="Uses public web data.",
    tools=[tool],
)
n8n
{
  "nodes": [
    {
      "name": "Run arcadium/tripadvisor-reviews",
      "type": "n8n-nodes-base.httpRequest",
      "typeVersion": 4,
      "position": [
        0,
        0
      ],
      "parameters": {
        "method": "POST",
        "url": "https://api.apify.com/v2/acts/arcadium~tripadvisor-reviews/run-sync-get-dataset-items",
        "authentication": "genericCredentialType",
        "genericAuthType": "httpHeaderAuth",
        "sendBody": true,
        "specifyBody": "json",
        "jsonBody": "{\"startUrls\":[{\"url\":\"https://www.tripadvisor.com/Hotel_Review-g60763-d93450-Reviews-Hyatt_Grand_Central_New_York-New_York_City_New_York.html\"}],\"maxReviewsPerPlace\":20}",
        "options": {
          "timeout": 300000
        }
      }
    }
  ],
  "connections": {}
}
Google Sheets
// Extensions > Apps Script. Store your token once: Project Settings > Script properties > APIFY_TOKEN.
function importLastRun() {
  const token = PropertiesService.getScriptProperties().getProperty('APIFY_TOKEN');
  const url = 'https://api.apify.com/v2/acts/arcadium~tripadvisor-reviews/runs/last/dataset/items?status=SUCCEEDED&clean=true&format=json';
  const res = UrlFetchApp.fetch(url, { headers: { Authorization: 'Bearer ' + token } });
  const rows = JSON.parse(res.getContentText());
  if (!rows.length) return;
  const keys = Object.keys(rows[0]);
  const values = rows.map((r) => keys.map((k) => (typeof r[k] === 'object' ? JSON.stringify(r[k]) : r[k])));
  const sheet = SpreadsheetApp.getActiveSheet();
  sheet.clearContents();
  sheet.getRange(1, 1, 1, keys.length).setValues([keys]);
  sheet.getRange(2, 1, values.length, keys.length).setValues(values);
}

Limitations

FAQ

How fresh is the data? It is read when you run the actor, so it matches what the site shows at that moment.

Can I get only new reviews since my last run? Yes. Turn on onlyNewReviews and keep the same stateKey between runs. Reviews you already received are skipped and not charged. The state lives in a key-value store in your Apify account. Pick a new stateKey to start over.

Does the actor store anything in my account? Yes, one small named key-value store, tripadvisor-reviews-state. It caches the identifiers of Tripadvisor's own review queries so the next run starts faster, and it holds the onlyNewReviews state. It contains no review text.

A place returned no reviews. Why? Check that the URL opens a hotel, restaurant or attraction page in your browser. Places without reviews return a free error row.

Something looks wrong in the output. Who do I tell? Open an issue on the actor page with the run link. We read them all.

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