# iRecommend Search Scraper (`powerai/irecommend-search-scraper`) Actor Scrape product recommendations from iRecommend.ru with automatic pagination and comprehensive review data extraction. - **URL**: https://apify.com/powerai/irecommend-search-scraper.md - **Developed by:** [PowerAI](https://apify.com/powerai) (community) - **Categories:** E-commerce, Lead generation, Automation - **Stats:** 7 total users, 3 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing from $4.99 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event ## What's an Apify Actor? An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes. 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. Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md. ## 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. Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run. For examples already wired to this Actor's own input schema, see the [API](#api) section below. Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`). # README ## 💬 iRecommend Search Scraper This actor allows you to scrape product recommendations from iRecommend.ru by providing a search URL. It automatically handles pagination and extracts comprehensive product information including ratings, reviews, votes, and user feedback. ### Features - **URL-based Scraping:** Extract product recommendations by providing a complete iRecommend search URL - **Automatic Pagination:** Automatically navigates through pages and loads more results until reaching the end or max items limit - **Comprehensive Product Data:** Extract detailed information about each product including: - Product names and detail page links - Average ratings and total votes - Review counts and links to all reviews - Product images - Review extracts and summaries - User engagement metrics (likes and dislikes) - **Smart Deduplication:** Automatically removes duplicate products based on detail page URLs ### Input Parameters | Field | Type | Required | Description | |------------|---------|----------|------------------------------------------------| | `searchUrl`| string | Yes | Complete iRecommend.ru search URL to scrape | | `maxItems` | integer | No | Maximum number of products to fetch | | `proxyConfiguration` | object | No | Proxy settings for the actor | #### How to Get Search URL 1. Go to [iRecommend.ru](https://irecommend.ru) 2. Use the search bar to find products or recommendations 3. Copy the complete URL from your browser's address bar 4. Paste it into the `searchUrl` field Example search URLs: ``` https://irecommend.ru/srch?query=iphone https://irecommend.ru/srch?query=laptop https://irecommend.ru/srch?query=cosmetics ``` ### Output The output is a dataset of product recommendation objects, each containing: - `searchUrl`: The original search URL used - `name`: Product name - `detailPageUrl`: Direct link to the product detail page - `allReviewsLink`: Link to all reviews for the product - `reviewCount`: Total number of reviews - `image`: URL of the product image - `extract`: Review extract or summary text - `extractUrl`: Link to the full review extract - `averageRating`: Average rating score (e.g., 4.8) - `votes`: Total number of votes - `likes`: Number of likes - `dislikes`: Number of dislikes - `scrapedAt`: Timestamp of when the product was scraped Example output: ```json [ { "searchUrl": "https://irecommend.ru/srch?query=iphone", "name": "Смартфон Apple Iphone 13 Pro Max", "detailPageUrl": "https://irecommend.ru/content/mobilnyi-telefon-apple-iphone-13-pro-max", "allReviewsLink": "https://irecommend.ru/content/mobilnyi-telefon-apple-iphone-13-pro-max", "reviewCount": 145, "image": "https://cdn-irec.r-99.com/sites/default/files/imagecache/150o/product-images/10297/7zAaSH9No8RzMu3c2I7rVw.jpg", "extract": "использовала айфон 16 pro max и 13 pro max вместе неделю. Плюс общие впечатления о айфоне 13 pro max спустя 3 года использования", "extractUrl": "https://irecommend.ru/content/ispolzovala-aifon-16-pro-max-i-13-pro-max-vmeste-nedelyu-plyus-obshchie-vpechatleniya-o-aifo", "averageRating": 4.8, "votes": 145, "likes": 143, "dislikes": 2, "scrapedAt": "2025-11-10T06:26:31.684Z" }, ... ] ``` ### Use Cases - Product research and comparison - Consumer sentiment analysis - Market research and trend analysis - Review aggregation and analysis - Product recommendation tracking - Competitive analysis for brands - User feedback collection ### Notes - The actor works with iRecommend.ru (Russian product recommendation platform) - Results are automatically paginated until reaching the end or max items limit - All ratings and counts are extracted as numbers for easy analysis - Product images and review extracts provide rich context for each recommendation - The actor includes delays between actions to ensure reliable scraping *** **Start scraping product recommendations from iRecommend.ru today!** # Actor input Schema ## `searchUrl` (type: `string`): The complete iRecommend.ru search URL to scrape ## `maxItems` (type: `integer`): Maximum number of products to fetch ## `proxyConfiguration` (type: `object`): Proxy settings for the actor ## Actor input object example ```json { "searchUrl": "https://irecommend.ru/srch?query=iphone", "maxItems": 100, "proxyConfiguration": { "useApifyProxy": false, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ``` # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("powerai/irecommend-search-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 = {} # Run the Actor and wait for it to finish run = client.actor("powerai/irecommend-search-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}") for item in client.dataset(run.default_dataset_id).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call powerai/irecommend-search-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,powerai/irecommend-search-scraper" } } } ``` The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer ` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations). ## OpenAPI specification Download the OpenAPI definition: https://api.apify.com/v2/actors/rMWALlhZKBXeMVKbA/builds/AW0uWxjE5wvKYtXZe/openapi.json