# Steam Reviews Scraper (`powerai/steam-reviews-scraper`) Actor Scrape game reviews from Steam Community with comprehensive review data including ratings, helpful counts, author information, and developer responses. - **URL**: https://apify.com/powerai/steam-reviews-scraper.md - **Developed by:** [PowerAI](https://apify.com/powerai) (community) - **Categories:** Automation, Lead generation, Developer tools - **Stats:** 4 total users, 0 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? Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. 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. - **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use). - **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`. - **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`. - **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`. - **Any other language** — 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 ## 🎮 Steam Reviews Scraper This actor allows you to scrape game reviews from Steam Community by providing a reviews page URL. It automatically handles pagination and extracts comprehensive review information including ratings, helpful counts, author details, and developer responses. ### Features - **URL-based Scraping:** Extract reviews by providing a complete Steam Community reviews page URL - **Automatic Pagination:** Automatically scrolls and loads more reviews until reaching the end or max items limit - **Comprehensive Review Data:** Extract detailed information about each review including: - Review text and title - Recommendation status (Recommended/Not Recommended) - Helpful count and award count - Hours played on record - Review date - Author information (name, profile, avatar, products owned) - Developer responses - Comment counts - **Smart Deduplication:** Automatically removes duplicate reviews based on detail page URLs ### Input Parameters | Field | Type | Required | Description | |----------------------|---------|----------|------------------------------------------------| | `searchUrl` | string | Yes | Complete Steam Community reviews page URL | | `maxItems` | integer | No | Maximum number of reviews to fetch (default: unlimited) | | `proxyConfiguration` | object | No | Proxy settings for the actor | #### How to Get Reviews URL 1. Go to [Steam Community](https://steamcommunity.com) 2. Navigate to any game's reviews page 3. You can filter by different criteria (Most Helpful, Recent, etc.) 4. Copy the complete URL from your browser's address bar 5. Paste it into the `searchUrl` field Example review URLs: ``` https://steamcommunity.com/app/3581600/reviews/?browsefilter=toprated&snr=1_5_100010_ https://steamcommunity.com/app/730/reviews/?browsefilter=mostrecent https://steamcommunity.com/app/271590/reviews/?browsefilter=mosthelpful ``` ### Output The output is a dataset of review objects, each containing: - `searchUrl`: The original reviews page URL used - `detailPageUrl`: Direct link to the review detail page - `helpfulCount`: Number of people who found the review helpful - `awardCount`: Number of awards given to the review - `isRecommended`: Boolean indicating if the review recommends the game - `recommendedType`: Type of recommendation ("positive" or "negative") - `hoursOnRecord`: Number of hours the reviewer has played the game - `title`: Review title ("Recommended" or "Not Recommended") - `datePosted`: Date when the review was posted - `reviewText`: The actual review content - `developerResponse`: Developer's response to the review (if available) - `author`: Author information object containing: - `name`: Reviewer's Steam username - `profileUrl`: Link to reviewer's Steam profile - `avatar`: URL of reviewer's avatar image - `productsInAccount`: Number of products in reviewer's account - `commentsCount`: Number of comments on the review - `scrapedAt`: Timestamp of when the review was scraped Example output: ```json [ { "searchUrl": "https://steamcommunity.com/app/3581600/reviews/?browsefilter=toprated&snr=1_5_100010_", "detailPageUrl": "https://steamcommunity.com/id/sinecostan/recommended/3581600/", "helpfulCount": 11, "awardCount": 0, "isRecommended": true, "recommendedType": "negative", "hoursOnRecord": 0.2, "title": "Not Recommended", "datePosted": "13 August", "reviewText": "mobile trash ported to steam, yucky do not play", "developerResponse": "A developer has responded to this review", "author": { "name": "Vitamin R", "profileUrl": "https://steamcommunity.com/id/sinecostan/", "avatar": "https://avatars.akamai.steamstatic.com/cd36dde8ac34e76ff9fd5731c380e1474d14684e.jpg", "productsInAccount": "2,164 products in account" }, "commentsCount": 0, "scrapedAt": "2025-11-11T08:28:58.633Z" }, ... ] ``` ### Use Cases - Game review analysis and sentiment tracking - Competitive research for game developers - Review quality assessment - Customer feedback analysis - Market research for gaming industry - Review moderation and monitoring - Developer response tracking - Review helpfulness analysis ### Notes - Results are automatically paginated until reaching the end or max items limit - All timestamps are in ISO 8601 format - The actor handles network delays and timeouts gracefully - Reviews are deduplicated based on their detail page URLs - Developer responses are included when available - Hours played information helps assess review credibility *** **Start scraping game reviews from Steam Community today!** # Actor input Schema ## `searchUrl` (type: `string`): The complete Steam Community reviews page URL to scrape ## `maxItems` (type: `integer`): Maximum number of reviews to fetch ## `proxyConfiguration` (type: `object`): Proxy settings for the actor ## Actor input object example ```json { "searchUrl": "https://steamcommunity.com/app/3581600/reviews/?browsefilter=toprated&snr=1_5_100010_", "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/steam-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 = {} # Run the Actor and wait for it to finish run = client.actor("powerai/steam-reviews-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/steam-reviews-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,powerai/steam-reviews-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/VgZJ64HLs0kuyQrhy/builds/0G5l8khWDc9npvasy/openapi.json