# Amazon Reviews Scraper (`scrapeai/amazon-reviews-scraper`) Actor Extract customer reviews from Amazon products, including review text, star ratings, helpful vote counts, verified purchase indicators, and reviewer details. - **URL**: https://apify.com/scrapeai/amazon-reviews-scraper.md - **Developed by:** [ScrapeAI](https://apify.com/scrapeai) (community) - **Categories:** E-commerce, Developer tools, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $10.00 / 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/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 ## Amazon Reviews Scraper Scrape Amazon.in product reviews at scale using product page URLs as input. Automatically identifies product ASINs, opens review pages, and collects reviewer feedback, ratings, timestamps, purchase verification status, and helpfulness metrics. ### Features - **Smart ASIN extraction** — automatically identifies product ASINs from Amazon India URLs - **Review-page prioritization** — attempts direct review page scraping before falling back to product pages when needed - **Continuous pagination support** — traverses multiple review pages to maximize review collection - **Enhanced review metadata** — extracts review content, ratings, titles, usernames, dates, verified badges, helpful votes, and attached images - **CAPTCHA monitoring** — logs anti-bot challenges while maintaining scraper stability - **Cloud automation ready** — deploy seamlessly on Apify with scheduling and proxy infrastructure ### Example Input ```json { "productUrls": [ "https://www.amazon.in/dp/B0DGJ6FKJN" ], "maxReviewsPerProduct": 10 } ```` #### Example Output ```json { "reviewId": "R2A82TM4IN10OR", "rating": 1, "reviewTitle": "Excellent noise cancellation and sound quality", "reviewText": "Bought these headphones for my work from home setup. The noise cancellation is phenomenal — blocks out all background noise. Sound quality is crystal clear for both music and calls.", "reviewerName": "Alpha Lion", "reviewerProfileUrl": "https://www.amazon.in/gp/profile/amzn1.account.AETWHFQJT246IP5OU27WDYI4Y4DA", "reviewDate": "Reviewed in India on 14 May 2025", "verifiedPurchase": true, "helpfulVotes": 177, "reviewImages": [], "productAsin": "B0DGJ6FKJN", "productTitle": "Apple iPhone 16 Pro Max 1 TB: 5G Mobile Phone with Camera Control, 4K 120 fps Dolby Vision and a Huge Leap in Battery Life. Works with AirPods; White Titanium", "productRating": "4.4 out of 5 stars", "totalReviews": 489, "productUrl": "https://www.amazon.in/dp/B0DGJ6FKJN", "reviewUrl": "https://www.amazon.in/gp/customer-reviews/R2A82TM4IN10OR", "scrapedAt": "2026-05-27T10:29:22.569Z" } ``` # Actor input Schema ## `productUrls` (type: `array`): Array of Amazon India product URLs to scrape reviews from. ASIN is extracted automatically from the URL. ## `maxReviewsPerProduct` (type: `integer`): Maximum number of reviews to scrape per product. Note: Due to Amazon.in restrictions, only ~6-10 top reviews are available on the product page without login. ## `headless` (type: `boolean`): Run browser in headless mode (no visible UI). Set to false for debugging. ## `proxyConfiguration` (type: `object`): Use Apify Proxy or custom HTTP proxy to avoid IP blocking. Residential proxies with India country are recommended. ## Actor input object example ```json { "productUrls": [ "https://www.amazon.in/dp/B0DGJ6FKJN" ], "maxReviewsPerProduct": 10, "headless": true, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "IN" } } ``` # 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 = { "productUrls": [ "https://www.amazon.in/dp/B0DGJ6FKJN" ], "maxReviewsPerProduct": 10, "headless": true }; // Run the Actor and wait for it to finish const run = await client.actor("scrapeai/amazon-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 = { "productUrls": ["https://www.amazon.in/dp/B0DGJ6FKJN"], "maxReviewsPerProduct": 10, "headless": True, } # Run the Actor and wait for it to finish run = client.actor("scrapeai/amazon-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 '{ "productUrls": [ "https://www.amazon.in/dp/B0DGJ6FKJN" ], "maxReviewsPerProduct": 10, "headless": true }' | apify call scrapeai/amazon-reviews-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapeai/amazon-reviews-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Amazon Reviews Scraper", "description": "Extract customer reviews from Amazon products, including review text, star ratings, helpful vote counts, verified purchase indicators, and reviewer details.", "version": "1.0", "x-build-id": "Y2hHhtdzXy4YXgymh" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapeai~amazon-reviews-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapeai-amazon-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrapeai~amazon-reviews-scraper/runs": { "post": { "operationId": "runs-sync-scrapeai-amazon-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrapeai~amazon-reviews-scraper/run-sync": { "post": { "operationId": "run-sync-scrapeai-amazon-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "productUrls" ], "properties": { "productUrls": { "title": "Product URLs", "type": "array", "description": "Array of Amazon India product URLs to scrape reviews from. ASIN is extracted automatically from the URL.", "items": { "type": "string" } }, "maxReviewsPerProduct": { "title": "Max Reviews Per Product", "minimum": 1, "maximum": 50, "type": "integer", "description": "Maximum number of reviews to scrape per product. Note: Due to Amazon.in restrictions, only ~6-10 top reviews are available on the product page without login.", "default": 10 }, "headless": { "title": "Headless Mode", "type": "boolean", "description": "Run browser in headless mode (no visible UI). Set to false for debugging.", "default": true }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Use Apify Proxy or custom HTTP proxy to avoid IP blocking. Residential proxies with India country are recommended.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "IN" } } } }, "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 } } } } } } } } } } ```