# Steam Scraper (`great_pistachio/steam-scraper`) Actor Scrape the Steam store with no login. Three modes: search apps by name, pull full app details (developer, publisher, genres, price, release date, Metacritic, platforms), and fetch customer reviews with cursor pagination. For game market research, competitor tracking, and review mining. - **URL**: https://apify.com/great\_pistachio/steam-scraper.md - **Developed by:** [Saturnin Pugnet](https://apify.com/great_pistachio) (community) - **Categories:** E-commerce - **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 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 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. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ## Steam Scraper - Games, Details & Reviews Scrape the [Steam](https://store.steampowered.com) store over its public JSON endpoints. **No login, no API key.** Three modes for game market research, competitor tracking, and review mining. ### Modes | Mode | What it does | Needs | |------|--------------|-------| | `search` | Find apps/games by name (returns app IDs) | `searchTerm` | | `details` | Full app metadata (dev, publisher, genres, price, Metacritic, platforms) | `appIds` | | `reviews` | Customer reviews with cursor pagination | `appIds` | ### Input ```json { "mode": "search", "searchTerm": "portal" } ```` ```json { "mode": "details", "appIds": ["620", "440"], "country": "us" } ``` ```json { "mode": "reviews", "appIds": ["620"], "reviewFilter": "recent", "maxReviewsPerApp": 500 } ``` | Field | Description | |-------|-------------| | `mode` | `details`, `reviews`, or `search` | | `appIds` | Numeric Steam app IDs (find them with `search`) | | `searchTerm` | App/game name for `search` | | `reviewFilter` | `recent`, `updated`, or `all` | | `language` | Review language (e.g. `english`, `all`) | | `country` | Two-letter code for pricing (`us`, `gb`, `de`) | | `maxReviewsPerApp` | Cap per app. 0 = unlimited | | `maxResults` | Overall cap. 0 = unlimited | ### Output **Apps:** `appId`, `name`, `type`, `developers`, `publishers`, `genres`, `categories`, `isFree`, `price`, `currency`, `discountPercent`, `releaseDate`, `metacriticScore`, `recommendationsTotal`, `platforms`, `shortDescription`, `website`, `appUrl`. **Reviews:** `appId`, `recommendationId`, `authorSteamId`, `authorPlaytimeForeverMin`, `authorNumGamesOwned`, `language`, `review`, `votedUp`, `votesUp`, `votesFunny`, `weightedVoteScore`, `steamPurchase`, `timestampCreated`. ### Related Actors - [Apple App Store Scraper](https://apify.com/great_pistachio/apple-app-store-scraper) - [Website Company Enricher](https://apify.com/great_pistachio/website-company-enricher) # Actor input Schema ## `mode` (type: `string`): What to scrape. ## `appIds` (type: `array`): Numeric Steam app IDs (e.g. 620 for Portal 2). Required for details and reviews. Find IDs with the Search mode. ## `searchTerm` (type: `string`): For the Search mode: game/app name to search for. ## `reviewFilter` (type: `string`): For the Reviews mode: which reviews to pull. ## `language` (type: `string`): For the Reviews mode: review language (Steam language code, or 'all'). ## `country` (type: `string`): Two-letter country code for pricing (details/search), e.g. us, gb, de. ## `maxReviewsPerApp` (type: `integer`): Cap reviews pulled per app. 0 = unlimited (can be very large). ## `maxResults` (type: `integer`): Overall cap across all apps. 0 = unlimited. ## Actor input object example ```json { "mode": "details", "appIds": [ "620" ], "searchTerm": "", "reviewFilter": "recent", "language": "english", "country": "us", "maxReviewsPerApp": 200, "maxResults": 0 } ``` # Actor output Schema ## `defaultDataset` (type: `string`): Steam apps (name, developer, genres, price, Metacritic, platforms) and customer reviews (voted up, playtime, text) # 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 = { "appIds": [ "620" ] }; // Run the Actor and wait for it to finish const run = await client.actor("great_pistachio/steam-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 = { "appIds": ["620"] } # Run the Actor and wait for it to finish run = client.actor("great_pistachio/steam-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 '{ "appIds": [ "620" ] }' | apify call great_pistachio/steam-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=great_pistachio/steam-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Steam Scraper", "description": "Scrape the Steam store with no login. Three modes: search apps by name, pull full app details (developer, publisher, genres, price, release date, Metacritic, platforms), and fetch customer reviews with cursor pagination. For game market research, competitor tracking, and review mining.", "version": "1.0", "x-build-id": "ZrUQPghgwJXMAgYDa" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/great_pistachio~steam-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-great_pistachio-steam-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/great_pistachio~steam-scraper/runs": { "post": { "operationId": "runs-sync-great_pistachio-steam-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/great_pistachio~steam-scraper/run-sync": { "post": { "operationId": "run-sync-great_pistachio-steam-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "mode" ], "properties": { "mode": { "title": "Mode", "enum": [ "details", "reviews", "search" ], "type": "string", "description": "What to scrape.", "default": "details" }, "appIds": { "title": "App IDs", "type": "array", "description": "Numeric Steam app IDs (e.g. 620 for Portal 2). Required for details and reviews. Find IDs with the Search mode.", "default": [ "620" ], "items": { "type": "string" } }, "searchTerm": { "title": "Search Term", "type": "string", "description": "For the Search mode: game/app name to search for.", "default": "" }, "reviewFilter": { "title": "Review Filter", "enum": [ "recent", "updated", "all" ], "type": "string", "description": "For the Reviews mode: which reviews to pull.", "default": "recent" }, "language": { "title": "Review Language", "type": "string", "description": "For the Reviews mode: review language (Steam language code, or 'all').", "default": "english" }, "country": { "title": "Country / Currency", "type": "string", "description": "Two-letter country code for pricing (details/search), e.g. us, gb, de.", "default": "us" }, "maxReviewsPerApp": { "title": "Max Reviews per App", "minimum": 0, "type": "integer", "description": "Cap reviews pulled per app. 0 = unlimited (can be very large).", "default": 200 }, "maxResults": { "title": "Max Results Total", "minimum": 0, "type": "integer", "description": "Overall cap across all apps. 0 = unlimited.", "default": 0 } } }, "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 } } } } } } } } } } ```