Steam Store Scraper ๐ŸŽฎ (price, reviews, metadata) avatar

Steam Store Scraper ๐ŸŽฎ (price, reviews, metadata)

Pricing

from $0.70 / 1,000 app founds

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Steam Store Scraper ๐ŸŽฎ (price, reviews, metadata)

Steam Store Scraper ๐ŸŽฎ (price, reviews, metadata)

Scrape Steam store pages for price, discount, developer, genres, platforms, Metacritic score, release date and review scores by search term or app ID, plus unlimited individual reviews with language and sentiment filters. No login, no browser, no API key needed.

Pricing

from $0.70 / 1,000 app founds

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Tagada Data

Tagada Data

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Steam Store Scraper ๐ŸŽฎ (price, reviews and metadata)

Scrape the Steam store into clean JSON: game metadata, pricing, and unlimited reviews. Give a search term or an app ID and this actor returns the full store record, including price & discount, developer, publisher, genres, platforms, Metacritic, release date and a review-score summary, plus, on demand, every review of a game via cursor pagination. It runs straight off Steam's public JSON endpoints, so there's no login, no browser, no API key to worry about.

Built for game market research, price & discount monitoring, review sentiment analysis, competitive tracking and AI agents (REST API + MCP).

Why this Steam scraper

Most Steam actors either scrape metadata or reviews, and cap reviews at a few dozen. This one does both in one actor and removes the cap: you can download all reviews of a game (hundreds of thousands of them) as individual dataset items, with the filters review analysis actually needs.

  • ๐Ÿ” Unlimited reviews: pagination runs on cursors, so you can pull up to 1,000,000 reviews per app, each saved as its own type: "review" record.
  • ๐ŸŽ›๏ธ You can filter reviews by language, positive or negative, purchase type, date range and sort order.
  • ๐Ÿท๏ธ Full metadata and pricing come together too, covering regional price, discount, Metacritic, genres, platforms and release date.
  • ๐Ÿ’ธ Cheap and no browser required: app metadata runs at $1/1,000, reviews at $0.40/1,000.

What you can do with it

  • For review sentiment analysis, pull every review for a game (text, votes, helpfulness, author playtime) and feed it into NLP or an LLM.
  • Use it for price and discount monitoring by tracking a list of app IDs across regions and catching sales as they happen.
  • Game market research gets easier too: genres, developers, Metacritic scores and review scores across a search term or a whole catalog.
  • Competitive tracking: compare titles by review score, recommendation counts and pricing.
  • Or simply feed AI agents structured Steam data over REST or MCP.

What you get

  • โœ… Pricing: current and original price, discount percentage and currency, in any country region you pick.
  • โœ… Catalog data covering developer, publisher, genres, categories, platforms, release date and Metacritic.
  • โœ… A review pulse: aggregate score (things like Overwhelmingly Positive), positive/negative/total counts, and positive percentage.
  • โœ… Unlimited reviews (optional): every review of a game via cursor pagination, with full text, votes, helpfulness score, author playtime and stats, and timestamps. Filter by language, positive/negative, purchase type and date range.
  • โœ… Search or go straight by ID: discover apps by term, or enrich exact app IDs and store URLs.
  • โœ… Filters for type, free-only, minimum reviews and maximum price.

Quick start

Search and keep only well-reviewed games:

{
"searchTerms": ["roguelike", "city builder"],
"types": ["game"],
"minReviews": 500,
"includeReviewSummary": true,
"maxResults": 200
}

Download all reviews of specific games (each review = one dataset item):

{
"appIds": ["400", "620"],
"maxReviewsPerApp": 1000000,
"reviewLanguage": "english"
}

Output (per app)

{
"source": "Steam",
"appId": "400",
"name": "Portal",
"type": "game",
"url": "https://store.steampowered.com/app/400",
"isFree": false,
"currency": "USD",
"priceInitial": 9.99,
"priceFinal": 1.99,
"discountPercent": 80,
"developers": ["Valve"],
"publishers": ["Valve"],
"genres": ["Action"],
"platforms": { "windows": true, "mac": false, "linux": true },
"metacriticScore": 90,
"releaseDate": "Oct 10, 2007",
"reviewScoreDesc": "Overwhelmingly Positive",
"totalReviews": 196159,
"totalPositive": 193260,
"positivePercent": 99,
"recommendations": 170784,
"scrapedAt": "2026-07-05T20:10:00.000Z"
}

Pricing

Pay per event, no subscription:

EventPriceWhen
App found$1.00 / 1,000Per app record returned
Review scraped$0.40 / 1,000Per individual review item (only when maxReviewsPerApp > 0)

Apify platform usage (compute) is billed separately at platform rates. No proxy is required.

FAQ

How do I download ALL reviews of a Steam game? Set maxReviewsPerApp high (up to 1,000,000) and reviews stream out as separate type: "review" items at $0.40/1,000. A 100k-review dump costs about $40 in events. The aggregate score summary is on the app record by default at no extra event cost.

Can I filter reviews? Yes, by reviewLanguage, reviewType (positive/negative) and reviewDayRange (e.g. only the last 30 days).

How are apps discovered? searchTerms use Steam's store search; you can also pass exact appIds or store URLs.

Which region's price? Set country (e.g. fr, de) and the price and currency will follow it.

How do I export the data? Use the Apify dataset export (CSV, Excel, JSON) or the API .../dataset/items?format=csv.

Is it reliable? These are Steam's own public JSON endpoints. The actor stays polite (low concurrency) and retries on rate limits, and delisted or region-locked apps are skipped rather than failing the run.

Can I use it with AI agents? Yes, both REST API and MCP are supported.


Something missing?

If you need an extra field, another source, or a different output, open an issue on this Actor and describe it. I read every request and small additions usually ship within days. More data and lead generation Actors are on my profile.

Keywords: steam scraper, steam store scraper, steam api, steam reviews scraper, download steam reviews, steam price monitoring, steam sentiment analysis, metacritic, game market research, steam appdetails, appreviews, MCP.