# Steam Reviews Scraper (`straightforward_hydra/steam-reviews-scraper`) Actor Scrape reviews for any Steam game: recommendation (thumbs up/down), text, playtime, helpfulness, author and dates, by app ID or game name. Official Steam API, no key needed. - **URL**: https://apify.com/straightforward\_hydra/steam-reviews-scraper.md - **Developed by:** [Dev D](https://apify.com/straightforward_hydra) (community) - **Categories:** Social media, Automation, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.00 / 1,000 reviews 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/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 Reviews Scraper 🎮 **Scrape reviews for any Steam game — recommendation (thumbs up/down), text, playtime, helpfulness, author and dates — by app ID or game name. Official Steam API, no key required.** Steam reviews are a goldmine for game developers, publishers and market researchers. This Actor pulls reviews for one or more games straight from Steam's official public reviews endpoint, with filters for language, review type and sort order, and returns clean structured records — including each reviewer's **playtime** and whether they recommend the game. > Uses Steam's official public reviews API — no key, no login, no browser. --- ### What you can do with it - 🎮 **Track your game's reviews** — monitor sentiment, catch complaints, measure updates. - 🕵️ **Competitor analysis** — see what players love and hate about other games. - 🗣️ **Voice of player** — mine feedback, bugs and feature requests. - 📊 **Market research** — analyze reviews, playtime and recommendation rates. - 🔔 **Review alerts** — run on a schedule and push negative reviews to Slack. ### Features - ✅ **No API key** — official Steam endpoint, works out of the box. - ✅ **By app ID or game name** — pass IDs, or let it resolve names. - ✅ **Rich records** — recommendation, text, playtime, helpful/funny votes, purchase type, Steam Deck flag, author history. - ✅ **Filters** — language, positive/negative, sort by recent / updated / helpful. - ✅ **Low-maintenance** — official Steam API with cursor pagination. --- ### Finding a game's app ID The **app ID** is the number in the Steam store URL: `store.steampowered.com/app/`**`1245620`**`/ELDEN_RING` → app ID is `1245620`. Or just pass the game **name** and the Actor resolves it. ### Input | Field | Description | |---|---| | **Steam app IDs** | Numeric app IDs, e.g. `730`, `1245620`. | | **Game names** | Names to resolve automatically, e.g. `Elden Ring`. | | **Review language** | `all`, `english`, `german`, … | | **Sort / filter** | Most recent / recently updated / most helpful. | | **Review type** | All / positive only / negative only. | | **Purchase type** | All / Steam / non-Steam. | | **Max reviews per game** | Cap per game (default 200). | | **Max results** | Overall cap. | #### Example — recent negative reviews for a game ```json { "gameNames": ["Cyberpunk 2077"], "language": "english", "sortBy": "recent", "reviewType": "negative", "maxReviewsPerApp": 300 } ```` ### Output Each row is one review: ```json { "app_id": "1245620", "game_name": "ELDEN RING", "recommendation_id": "123456789", "language": "english", "review": "Incredible game, brutal but fair…", "voted_up": true, "votes_up": 42, "votes_funny": 3, "weighted_vote_score": 0.86, "comment_count": 1, "steam_purchase": true, "received_for_free": false, "written_during_early_access": false, "primarily_steam_deck": false, "created_at": "2026-07-10T18:03:22+00:00", "updated_at": "2026-07-10T18:03:22+00:00", "author_steamid": "7656119…", "author_num_games_owned": 120, "author_num_reviews": 8, "playtime_forever_min": 4200, "playtime_at_review_min": 4100, "playtime_last_two_weeks_min": 320 } ``` ### Run it on a schedule Schedule the Actor to pull new reviews daily, and connect a **Slack / email / webhook / Google Sheets** integration to route negative reviews to your team. ### Notes & limitations - Uses Steam's official public reviews API — no key needed. - Playtime is reported in minutes. - `voted_up` = the reviewer recommends the game (Steam has thumbs up/down, not star ratings). - This is **public review data**. *** #### Keywords Steam reviews, Steam scraper, game reviews, Steam review scraper, game reviews scraper, Steam data, game analytics, player reviews, gaming market research, review scraper, Steam API, game sentiment, voice of player, game feedback, Steam game data, review monitoring, gaming intelligence, user reviews, Steam store, game intelligence. # Actor input Schema ## `appIds` (type: `array`): Steam app IDs, e.g. 730 (Counter-Strike 2), 1245620 (Elden Ring). Find it in the store URL: store.steampowered.com/app/. ## `gameNames` (type: `array`): Game names to look up instead of IDs, e.g. "Elden Ring". The top matching game is used. Merged with the App IDs above. ## `language` (type: `string`): Steam language filter, e.g. all, english, french, german, schinese. Default all. ## `sortBy` (type: `string`): recent = newest first; updated = recently updated; all = by helpfulness. ## `reviewType` (type: `string`): Keep positive (recommended), negative (not recommended), or all reviews. ## `purchaseType` (type: `string`): Filter by how the reviewer got the game. ## `maxReviewsPerApp` (type: `integer`): Cap the number of reviews returned per game. Default 200. ## `maxResults` (type: `integer`): Stop after this many reviews in total. Leave empty for no limit. ## Actor input object example ```json { "appIds": [ "1245620" ], "language": "all", "sortBy": "recent", "reviewType": "all", "purchaseType": "all", "maxReviewsPerApp": 200 } ``` # 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": [ "1245620" ] }; // Run the Actor and wait for it to finish const run = await client.actor("straightforward_hydra/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 = { "appIds": ["1245620"] } # Run the Actor and wait for it to finish run = client.actor("straightforward_hydra/steam-reviews-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": [ "1245620" ] }' | apify call straightforward_hydra/steam-reviews-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=straightforward_hydra/steam-reviews-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Steam Reviews Scraper", "description": "Scrape reviews for any Steam game: recommendation (thumbs up/down), text, playtime, helpfulness, author and dates, by app ID or game name. Official Steam API, no key needed.", "version": "0.1", "x-build-id": "7MkVY0XFK1m7eI9sG" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/straightforward_hydra~steam-reviews-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-straightforward_hydra-steam-reviews-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/straightforward_hydra~steam-reviews-scraper/runs": { "post": { "operationId": "runs-sync-straightforward_hydra-steam-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/straightforward_hydra~steam-reviews-scraper/run-sync": { "post": { "operationId": "run-sync-straightforward_hydra-steam-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "appIds": { "title": "Steam app IDs", "type": "array", "description": "Steam app IDs, e.g. 730 (Counter-Strike 2), 1245620 (Elden Ring). Find it in the store URL: store.steampowered.com/app/.", "items": { "type": "string" } }, "gameNames": { "title": "Game names (resolved automatically)", "type": "array", "description": "Game names to look up instead of IDs, e.g. \"Elden Ring\". The top matching game is used. Merged with the App IDs above.", "items": { "type": "string" } }, "language": { "title": "Review language", "type": "string", "description": "Steam language filter, e.g. all, english, french, german, schinese. Default all.", "default": "all" }, "sortBy": { "title": "Sort / filter", "enum": [ "recent", "updated", "all" ], "type": "string", "description": "recent = newest first; updated = recently updated; all = by helpfulness.", "default": "recent" }, "reviewType": { "title": "Review type", "enum": [ "all", "positive", "negative" ], "type": "string", "description": "Keep positive (recommended), negative (not recommended), or all reviews.", "default": "all" }, "purchaseType": { "title": "Purchase type", "enum": [ "all", "steam", "non_steam_purchase" ], "type": "string", "description": "Filter by how the reviewer got the game.", "default": "all" }, "maxReviewsPerApp": { "title": "Max reviews per game", "minimum": 1, "type": "integer", "description": "Cap the number of reviews returned per game. Default 200.", "default": 200 }, "maxResults": { "title": "Max results", "minimum": 1, "type": "integer", "description": "Stop after this many reviews in total. Leave empty for no limit." } } }, "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 } } } } } } } } } } ```