# Steam Scraper — Game Details, Reviews & Player Counts (`samwise.agency/steam-intel`) Actor Scrape Steam: game details, prices, genres, Metacritic, live player counts, review scores and recent review text. Search by keyword or app ID. Official Steam endpoints — clean JSON/CSV for games market research. - **URL**: https://apify.com/samwise.agency/steam-intel.md - **Developed by:** [samwise.agency](https://apify.com/samwise.agency) (community) - **Categories:** Games - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 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 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 — Game Details, Reviews & Player Counts Market research for the biggest PC games platform. Search Steam or feed it app IDs, and get **game details, prices, genres, Metacritic scores, live player counts, and review sentiment** in clean rows. **What you can extract:** - 🎮 **Game details** — price, discount, developers, genres, release date, Metacritic - 👥 **Live player counts** — official concurrent-players API - 👍 **Review intelligence** — score summary + recent review text with playtime - 🔍 **Store search** — by niche ("cozy farming sim") or title ### Quick start 1. Click **Run** — default researches "roguelike deckbuilder" games 2. Swap in your genre or competitor titles 3. Schedule weekly = genre health tracking (players, review sentiment, pricing) ### Sample output ```json { "type": "game", "appId": 1091500, "name": "Cyberpunk 2077", "priceUsd": 29.99, "discountPercent": 50, "developers": ["CD PROJEKT RED"], "releaseDate": "Dec 10, 2020", "genres": ["RPG"], "metacritic": 86, "currentPlayers": 24812, "reviewScoreDesc": "Very Positive", "totalPositive": 512340, "totalNegative": 61023 } ```` ### Use cases - **Game studios & publishers** — competitive pricing and sentiment tracking - **Investors** — player-count trends as engagement signal - **Content creators** — data-backed "state of the genre" pieces - **Marketers** — find rising games before they're big ### Pricing Pay per result row (game or review). ### FAQ **Data sources?** Steam's own store endpoints and the official Steam Web API, fetched politely within rate limits. **Player count history?** Schedule the actor to build your own time series. # Actor input Schema ## `searchQueries` (type: `array`): Game names or niches to search the Steam store for (e.g. 'roguelike deckbuilder'). ## `appIds` (type: `array`): Specific games by app ID (e.g. 730 = Counter-Strike 2, 570 = Dota 2). ## `includePlayerCount` (type: `boolean`): Current concurrent players per game (official Steam Web API). ## `includeReviewSummary` (type: `boolean`): Review score description + positive/negative totals per game. ## `includeReviews` (type: `boolean`): Also export recent English reviews as separate rows (costs one result each). ## `maxReviewsPerGame` (type: `integer`): When review text is enabled. ## `maxSearchResults` (type: `integer`): Cost cap per search. ## Actor input object example ```json { "searchQueries": [ "roguelike deckbuilder" ], "appIds": [], "includePlayerCount": true, "includeReviewSummary": true, "includeReviews": false, "maxReviewsPerGame": 20, "maxSearchResults": 15 } ``` # 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 = { "searchQueries": [ "roguelike deckbuilder" ], "appIds": [] }; // Run the Actor and wait for it to finish const run = await client.actor("samwise.agency/steam-intel").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 = { "searchQueries": ["roguelike deckbuilder"], "appIds": [], } # Run the Actor and wait for it to finish run = client.actor("samwise.agency/steam-intel").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 '{ "searchQueries": [ "roguelike deckbuilder" ], "appIds": [] }' | apify call samwise.agency/steam-intel --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=samwise.agency/steam-intel", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Steam Scraper — Game Details, Reviews & Player Counts", "description": "Scrape Steam: game details, prices, genres, Metacritic, live player counts, review scores and recent review text. Search by keyword or app ID. Official Steam endpoints — clean JSON/CSV for games market research.", "version": "0.1", "x-build-id": "zpg9y6TXRMVfO9mXZ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/samwise.agency~steam-intel/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-samwise.agency-steam-intel", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/samwise.agency~steam-intel/runs": { "post": { "operationId": "runs-sync-samwise.agency-steam-intel", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/samwise.agency~steam-intel/run-sync": { "post": { "operationId": "run-sync-samwise.agency-steam-intel", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "searchQueries": { "title": "Search queries", "type": "array", "description": "Game names or niches to search the Steam store for (e.g. 'roguelike deckbuilder').", "default": [ "roguelike deckbuilder" ], "items": { "type": "string" } }, "appIds": { "title": "Steam app IDs", "type": "array", "description": "Specific games by app ID (e.g. 730 = Counter-Strike 2, 570 = Dota 2).", "default": [], "items": { "type": "string" } }, "includePlayerCount": { "title": "Include live player count", "type": "boolean", "description": "Current concurrent players per game (official Steam Web API).", "default": true }, "includeReviewSummary": { "title": "Include review summary", "type": "boolean", "description": "Review score description + positive/negative totals per game.", "default": true }, "includeReviews": { "title": "Include recent review text", "type": "boolean", "description": "Also export recent English reviews as separate rows (costs one result each).", "default": false }, "maxReviewsPerGame": { "title": "Max reviews per game", "minimum": 1, "maximum": 100, "type": "integer", "description": "When review text is enabled.", "default": 20 }, "maxSearchResults": { "title": "Max games per search query", "minimum": 1, "maximum": 50, "type": "integer", "description": "Cost cap per search.", "default": 15 } } }, "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 } } } } } } } } } } ```