# Amazon Urls Scraper (`getdataforme/amazon-urls-scraper`) Actor Extract detailed product data from Amazon URLs worldwide, including titles, prices, ratings, reviews, and specs. Leverages proxies for reliable scraping, delivers structured JSON output. Perfect for e-commerce analysis, competitive intelligence, and market research. - **URL**: https://apify.com/getdataforme/amazon-urls-scraper.md - **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community) - **Categories:** Automation, E-commerce, Lead generation - **Stats:** 7 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $9.00 / 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 Urls Scraper ### Introduction The Amazon Urls Scraper is a powerful Apify Actor designed to extract detailed product information from Amazon URLs. It efficiently scrapes data such as titles, descriptions, prices, ratings, and specifications from product pages across various Amazon domains. This tool is ideal for e-commerce professionals, researchers, and businesses needing accurate, structured data for analysis, monitoring, or integration into applications. ### Features - **Comprehensive Data Extraction**: Captures key product details including title, description, price, ratings, reviews, images, and specifications. - **Multi-Domain Support**: Works with Amazon URLs from different regions (e.g., .com, .de, .fr) for global scraping. - **Proxy Integration**: Utilizes residential proxies to avoid IP blocks and ensure reliable data collection. - **High Performance**: Built on CheerioCrawler for fast, efficient scraping with minimal resource usage. - **Structured Output**: Delivers clean JSON data, easily exportable to CSV, Excel, or databases. - **Error Handling**: Robust mechanisms to manage failed requests and retries for uninterrupted operation. - **Scalable**: Handles multiple URLs in a single run, supporting batch processing for large datasets. ### Input Parameters | Parameter | Type | Required | Description | Example | |-----------|------|----------|-------------|---------| | startUrls | array | Yes | An array of Amazon product URLs to scrape. Each URL should point to a specific product page. | `[{"url": "https://www.amazon.fr/-/en/Lenovo-Laptop-i5-13420H-1000GB-Windows/dp/B0DT7532C9/"}]` | | proxyConfiguration | object | Yes | Configuration for proxy servers to mask the scraper's IP and prevent blocking. Supports Apify Proxy with residential groups. | `{"useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"], "apifyProxyCountry": "US"}` | ### Example Usage #### Input JSON ```json { "startUrls": [ { "url": "https://www.amazon.de/-/en/Fantastic-Four-First-Steps-Blu-ray/dp/B0FS74TD6Q/" } ], "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"], "apifyProxyCountry": "US" } } ```` #### Output JSON ```json [ { "url": "https://www.amazon.de/-/en/Fantastic-Four-First-Steps-Blu-ray/dp/B0FS74TD6Q/?_encoding=UTF8&ref_=pd_hp_d_btf_crs_zg_bs_284266", "title": "The Fantastic Four - First Steps [Blu-ray]", "description": "A family. An incident. And suddenly: super powers! When a scientific experiment gets out of control, the lives of Reed Richards (Pedro Pascal), Sue Storm (Vanessa Kirby), Johnny Storm (Joseph Quinn), and Ben Grimm (Ebon Moss-Bachrach) changes forever. But with great power come great challenges. Forced to reconcile their roles as superheroes with the strength of their family ties, they must protect Earth from an enigmatic, namely galactic threat. And if Galactus' plan to destroy the entire planet wasn't bad enough, it also becomes very personal. Press Quotes: Popcorn cinema at its best. (FAMILIE.DE) \"The Fantastic Four take you into the space age 60s in this Marvel reboot with wit, great sets and entertaining family dynamics. [...] The casting of the titular four is flawless.\" (VISIONS.DE) \"The Fantastic Four are fantastic fun\" (GIGA.DE). Bonus material: Features: Get to know the first family, fantastic futurism, from the beyond and below, audio commentary by director Matt Shakman and scene designer Kasra Farahani, glitches from the shoot, deleted scenes", "price": "USD16.55", "rating": "4.0", "reviewCount": 96, "image": "https://m.media-amazon.com/images/I/51g2jdj4djL._SY300_SX300_QL70_ML2_.jpg", "specifications": { "Aspect Ratio ": "2.39:1", "Rated ": "Ages 12 and over", "Product Dimensions ": "13.7 x 1.5 x 16.6 cm; 60 g", "Director ": "Shakman, Matt", "Media Format ": "Blu-ray, Widescreen", "Run time ": "1 hour and 55 minutes", "Release date ": "31 Oct 2025", "Actors ": "Kirby, Vanessa, Malkovich, John, Moss-Bachrach, Ebon, Pascal, Pedro, Quinn, Joseph", "Subtitles: ": "Danish, Finnish, German, Norwegian, Swedish", "Language ": "German (DD 7.1 Plus)", "Studio ": "LEONINE", "ASIN ": "B0FS74TD6Q", "Country of origin ": "Germany", "Number of discs ": "1", "Customer reviews": "4.0 out of 5 stars 96 ratings" }, "scrapedAt": "2025-11-18T07:34:20.088Z" } ] ``` ### Use Cases - **Market Research**: Analyze product trends, pricing, and customer reviews across Amazon categories. - **Competitive Intelligence**: Monitor competitors' products, prices, and ratings for strategic insights. - **Price Monitoring**: Track price changes for e-commerce arbitrage or dynamic pricing strategies. - **Content Aggregation**: Build databases of product information for blogs, apps, or marketplaces. - **Academic Research**: Collect data on consumer goods for studies in economics or marketing. - **Business Automation**: Integrate scraped data into workflows for inventory management or sales forecasting. ### Installation and Usage 1. Search for "Amazon Urls Scraper" in the Apify Store 2. Click "Try for free" or "Run" 3. Configure input parameters 4. Click "Start" to begin extraction 5. Monitor progress in the log 6. Export results in your preferred format (JSON, CSV, Excel) ### Output Format The Actor outputs a JSON array of objects, each representing a scraped product. Key fields include: - `url`: The original Amazon product URL. - `title`: Product title. - `description`: Detailed product description. - `price`: Current price in USD or local currency. - `rating`: Average customer rating (e.g., "4.0"). - `reviewCount`: Number of reviews. - `image`: URL to the product image. - `specifications`: An object with detailed specs like dimensions, actors, and ASIN. - `scrapedAt`: Timestamp of scraping in ISO format. Data is structured for easy parsing and integration. ### Support For custom/simplified outputs or bug reports, please contact: - Email: support@getdataforme.com - Subject line: "custom support" - Contact form: https://getdataforme.com/contact/ We're here to help you get the most out of this Actor! # Actor input Schema ## `startUrls` (type: `array`): URLs to start with. ## `proxyConfiguration` (type: `object`): Specifies proxy servers that will be used by the scraper in order to hide its origin. ## Actor input object example ```json { "startUrls": [ { "url": "https://www.amazon.fr/-/en/Lenovo-Laptop-i5-13420H-1000GB-Windows/dp/B0DT7532C9/%22" } ], "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "US" } } ``` # 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.amazon.fr/-/en/Lenovo-Laptop-i5-13420H-1000GB-Windows/dp/B0DT7532C9/%22" } ], "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "US" } }; // Run the Actor and wait for it to finish const run = await client.actor("getdataforme/amazon-urls-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.amazon.fr/-/en/Lenovo-Laptop-i5-13420H-1000GB-Windows/dp/B0DT7532C9/%22" }], "proxyConfiguration": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], "apifyProxyCountry": "US", }, } # Run the Actor and wait for it to finish run = client.actor("getdataforme/amazon-urls-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.amazon.fr/-/en/Lenovo-Laptop-i5-13420H-1000GB-Windows/dp/B0DT7532C9/%22" } ], "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "US" } }' | apify call getdataforme/amazon-urls-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/amazon-urls-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Amazon Urls Scraper", "description": "Extract detailed product data from Amazon URLs worldwide, including titles, prices, ratings, reviews, and specs. Leverages proxies for reliable scraping, delivers structured JSON output. Perfect for e-commerce analysis, competitive intelligence, and market research.", "version": "0.0", "x-build-id": "imCT7KvEQp7laDhGb" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~amazon-urls-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-amazon-urls-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~amazon-urls-scraper/runs": { "post": { "operationId": "runs-sync-getdataforme-amazon-urls-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~amazon-urls-scraper/run-sync": { "post": { "operationId": "run-sync-getdataforme-amazon-urls-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "proxyConfiguration" ], "properties": { "startUrls": { "title": "Start URLs", "type": "array", "description": "URLs to start with.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "proxyConfiguration": { "title": "Select the Same Proxy configuration of which you want to use for scraping", "type": "object", "description": "Specifies proxy servers that will be used by the scraper in order to hide its origin.", "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 } } } } } } } } } } ```