# Tripadvisor Reviews Scraper (`cirkit/tripadvisor-reviews-scraper`) Actor Fast Tripadvisor reviews scraper. Drop in any hotel, restaurant, or attraction URL and get every review with full fields: rating, text, title, stay date, traveler type, language, reviewer profile, helpful votes, photos, mgmt response, and subratings. - **URL**: https://apify.com/cirkit/tripadvisor-reviews-scraper.md - **Developed by:** [Crikit](https://apify.com/cirkit) (community) - **Categories:** Real estate, SEO tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $3.50 / 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/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. 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. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use 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 Fast, reliable Tripadvisor reviews scraper for hotels, restaurants, and attractions. Drop in any Tripadvisor property URL and get every review back as clean JSON, ready to load into a database, BI tool, or LLM pipeline. No headless browser, no per-cookie setup, no user logins required. This actor is built for analysts, hospitality consultants, market researchers, and anyone who needs Tripadvisor review data at scale. It paginates through the full review history of a property and returns rich fields including the review body, star rating, traveler context, dates, language, reviewer profile, helpful votes, photos, management responses, and per-aspect subratings (hotels). ### What this Tripadvisor reviews scraper extracts For every review on a property, the actor returns: - Review ID, full text body, headline title, star rating (1 to 5) - Published date and original creation date (ISO 8601) - Stay or visit date and trip type (couples, family, solo, business, friends) - Language and original language codes (BCP-47) - Helpful vote count - Reviewer profile: display name, username, profile URL, hometown, avatar, total contributions, verified flag - Photo IDs and rendered photo URL templates for any images attached - Management or owner response: text, date, responder name, role - Per-aspect subratings (Value, Rooms, Location, Cleanliness, Service, Sleep Quality) for hotels - Direct deep link to the review page on Tripadvisor Every output field is camelCase JSON. The dataset schema declares each field so the Apify Console table view and the CSV / XLSX exports work out of the box. ### How it works The scraper reads Tripadvisor's server-rendered HTML once to seed the session and pull the first page of reviews for free. Pages two onward come from Tripadvisor's internal GraphQL endpoint at `/data/graphql/ids` using the persisted query id documented in our recon. Pagination is `limit / offset` with a 20-per-page server cap, and there is no upper depth limit, so the scraper happily walks the full review history of properties with tens of thousands of reviews. Anti-bot is handled automatically. The actor uses Safari TLS impersonation via curl_cffi and rotates through a pool of impersonation profiles when DataDome challenges appear. Apify Residential proxies in the US are recommended for production runs and are configured by default. ### Input Provide at least one Tripadvisor property URL in `startUrls`. URLs can be hotel, restaurant, or attraction listings on any Tripadvisor locale (`.com`, `.co.uk`, `.ca`, `.de`, etc.). ```json { "startUrls": [ {"url": "https://www.tripadvisor.com/Hotel_Review-g60763-d93437-Reviews-The_Plaza-New_York_City_New_York.html"} ], "maxReviewsPerProperty": 1000, "language": "en", "sortBy": "MOST_RECENT", "minRating": 0, "includePhotos": true } ```` Key inputs: - `startUrls` (required): one or more Tripadvisor property URLs. - `maxReviewsPerProperty` (default 1000): cap on reviews returned per property. - `language`: BCP-47 language filter, or leave empty for all languages. - `sortBy`: `MOST_RECENT`, `SERVER_DEFAULT`, or `MOST_FAVORABLE`. - `minRating`: only return reviews at or above this star value. - `includePhotos`: include photo URL templates and IDs on each review. - `proxyConfiguration`: Apify proxy config, defaults to US Residential. ### Output One record per review. Sample (truncated): ```json { "reviewId": 1060541589, "locationId": 93437, "propertyName": "Hotel Edison", "propertyType": "HOTEL", "title": "Birthday on Broadway", "text": "This trip was for my mother's 79th Birthday on Broadway...", "rating": 5, "publishedDate": "2026-05-12", "stayDate": "2026-04-30", "tripType": "FAMILY", "language": "en", "helpfulVotes": 3, "reviewerName": "Jane D", "reviewerHometown": "Atlanta, GA", "subratings": [ {"label": "Value", "rating": 5}, {"label": "Rooms", "rating": 5} ], "managementResponse": { "text": "Dear Jane, we thank you for staying...", "publishedDate": "2026-05-13", "responderName": "Rommel", "responderRole": "Guest Services / Front Office" }, "photos": [ {"id": 859139197, "urlTemplate": "https://...{width}x{height}...jpg"} ], "reviewUrl": "https://www.tripadvisor.com/ShowUserReviews-g60763-d93437-r1060541589-..." } ``` ### Pricing Flat pay-per-event pricing. You only pay for review records actually written to the dataset. No per-run fees, no minimums, no surprises. | Volume | Price | | ------ | ----- | | Per review | $0.0035 | | Per 1,000 reviews | $3.50 | Apify subscription tier discounts apply automatically. ### Use cases - Build a Tripadvisor review database for a hotel chain or restaurant brand for sentiment tracking - Monitor competitor reviews and management response cadence - Power LLM agents that summarize traveler feedback for property managers - Generate trend reports on traveler types, stay dates, and seasonal sentiment - Track aspect subratings over time (cleanliness, service, value) for revenue management - Enrich a hotel or restaurant CRM with verified guest review history - Feed review text into translation or analytics pipelines ### Tips for best results - Use Apify Residential proxies in the US (default). Datacenter proxies work for small runs but DataDome rotates blocks weekly. - Start with `maxReviewsPerProperty: 50` to confirm a target property is alive, then scale up. - For multi-property runs, pass an array of URLs in `startUrls`; the actor walks them sequentially and rotates sessions between properties. - If you only need the latest sentiment, set `sortBy: MOST_RECENT` and a small `maxReviewsPerProperty`. - Restaurant `locationId`s are sometimes recycled by Tripadvisor; if a known property returns zero reviews, search Tripadvisor again to get the current URL. - Subratings only appear on hotel reviews; restaurants and attractions return an empty array, as designed. ### Compliance This actor scrapes only public review pages and respects Tripadvisor's server-side review filters (verified, published, public). It does not attempt to access any private content or any data behind a login wall. The actor does not require any user-supplied cookies, session IDs, or login credentials. ### Support If a property returns zero reviews or the actor flags repeated DataDome blocks, leave a message on the actor issue tracker on Apify Console with the property URL. The recon notes for Tripadvisor are kept up to date and most issues resolve with a proxy refresh. # Actor input Schema ## `startUrls` (type: `array`): List of Tripadvisor property URLs to scrape reviews for. Accepts hotels, restaurants, and attractions. Example: https://www.tripadvisor.com/Hotel\_Review-g60763-d93437-Reviews-The\_Plaza-New\_York\_City\_New\_York.html ## `maxReviewsPerProperty` (type: `integer`): Upper bound on reviews returned per property. Server pages 20 at a time. Set to a small value for testing, larger for full pulls. ## `language` (type: `string`): Optional BCP-47 language code (en, es, fr, de, it, pt, ja, zh). Leave empty to return reviews in all languages. ## `sortBy` (type: `string`): How reviews are ordered before scraping. Most Recent walks newest-first. ## `minRating` (type: `integer`): Only return reviews with this rating or higher. 0 returns everything. Valid values: 0 to 5. ## `includePhotos` (type: `boolean`): When true, returns photo URL templates attached to each review. When false, only the photo ID list is returned. ## `proxyConfiguration` (type: `object`): US Residential proxies are required for sustained scraping. Datacenter works for small runs. ## Actor input object example ```json { "startUrls": [ { "url": "https://www.tripadvisor.com/Hotel_Review-g60763-d93437-Reviews-The_Plaza-New_York_City_New_York.html" } ], "maxReviewsPerProperty": 50, "language": "", "sortBy": "MOST_RECENT", "minRating": 0, "includePhotos": true, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "US" } } ``` # Actor output Schema ## `dataset` (type: `string`): Dataset of Tripadvisor review records. ## `datasetCsv` (type: `string`): Same dataset rendered as CSV. ## `datasetXlsx` (type: `string`): Same dataset rendered as XLSX. # 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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "startUrls": [ { "url": "https://www.tripadvisor.com/Hotel_Review-g60763-d93437-Reviews-The_Plaza-New_York_City_New_York.html" } ], "maxReviewsPerProperty": 50, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "US" } }; // Run the Actor and wait for it to finish const run = await client.actor("cirkit/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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "startUrls": [{ "url": "https://www.tripadvisor.com/Hotel_Review-g60763-d93437-Reviews-The_Plaza-New_York_City_New_York.html" }], "maxReviewsPerProperty": 50, "proxyConfiguration": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], "apifyProxyCountry": "US", }, } # Run the Actor and wait for it to finish run = client.actor("cirkit/tripadvisor-reviews-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).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-d93437-Reviews-The_Plaza-New_York_City_New_York.html" } ], "maxReviewsPerProperty": 50, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "US" } }' | apify call cirkit/tripadvisor-reviews-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=cirkit/tripadvisor-reviews-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Tripadvisor Reviews Scraper", "description": "Fast Tripadvisor reviews scraper. Drop in any hotel, restaurant, or attraction URL and get every review with full fields: rating, text, title, stay date, traveler type, language, reviewer profile, helpful votes, photos, mgmt response, and subratings.", "version": "0.2", "x-build-id": "YgFYVuELpOsb4OyeE" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/cirkit~tripadvisor-reviews-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-cirkit-tripadvisor-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/cirkit~tripadvisor-reviews-scraper/runs": { "post": { "operationId": "runs-sync-cirkit-tripadvisor-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/cirkit~tripadvisor-reviews-scraper/run-sync": { "post": { "operationId": "run-sync-cirkit-tripadvisor-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "startUrls" ], "properties": { "startUrls": { "title": "Tripadvisor Property URLs", "type": "array", "description": "List of Tripadvisor property URLs to scrape reviews for. Accepts hotels, restaurants, and attractions. Example: https://www.tripadvisor.com/Hotel_Review-g60763-d93437-Reviews-The_Plaza-New_York_City_New_York.html", "default": [], "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "maxReviewsPerProperty": { "title": "Max Reviews Per Property", "minimum": 1, "maximum": 50000, "type": "integer", "description": "Upper bound on reviews returned per property. Server pages 20 at a time. Set to a small value for testing, larger for full pulls.", "default": 1000 }, "language": { "title": "Review Language Filter", "enum": [ "", "en", "es", "fr", "de", "it", "pt", "ja", "zh", "ru", "nl" ], "type": "string", "description": "Optional BCP-47 language code (en, es, fr, de, it, pt, ja, zh). Leave empty to return reviews in all languages.", "default": "" }, "sortBy": { "title": "Sort Order", "enum": [ "MOST_RECENT", "SERVER_DEFAULT", "MOST_FAVORABLE" ], "type": "string", "description": "How reviews are ordered before scraping. Most Recent walks newest-first.", "default": "MOST_RECENT" }, "minRating": { "title": "Minimum Star Rating Filter", "minimum": 0, "maximum": 5, "type": "integer", "description": "Only return reviews with this rating or higher. 0 returns everything. Valid values: 0 to 5.", "default": 0 }, "includePhotos": { "title": "Include Photo URLs", "type": "boolean", "description": "When true, returns photo URL templates attached to each review. When false, only the photo ID list is returned.", "default": true }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "US Residential proxies are required for sustained scraping. Datacenter works for small runs.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "US" } } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```