Steam Reviews Scraper

Export public Steam game reviews with review text, sentiment, votes, playtime, language, purchase flags, timestamps, and author metadata.

Use this Actor when you need repeatable Steam review data for game research, player sentiment analysis, competitor monitoring, product feedback, localization analysis, or dashboards. Results can be downloaded as CSV, JSON, Excel, XML, RSS, or used through the Apify Dataset API.

At a glance

• Steam app input: scrape reviews by Steam app ID or public Steam store URL.
• Review text and sentiment: save review text, recommendation status, language, votes, and comment counts.
• Author and playtime data: include public author IDs, profile URLs, review counts, playtime, and last-played fields when available.
• Filtering controls: choose review order, language, review type, purchase type, and cursor.
• Continuation ready: use nextCursor to continue review collection from previous runs.

Ready-to-run examples

Use these saved Store examples as starting points. Open any example to prefill the Actor input, then adjust URLs, keywords, limits, or filters for your own run.

• Export Vampire Survivors Reviews
• Monitor Project Zomboid Reviews
• Export Raft Steam Reviews
• Build Subnautica Review Dataset
• Scrape Sons of the Forest Reviews
• Export Valheim Positive Reviews
• View all ready-to-run examples (50 examples)

What can it do?

Steam Reviews Scraper turns public Steam review feeds into structured review rows.

• Export Steam review data with text, recommendation status, votes, language, purchase flags, timestamps, and app IDs.
• Collect player context such as public author profile URL, Steam ID, review counts, games owned, and playtime when returned by Steam.
• Filter review feeds by language, sentiment, purchase type, and review ordering.
• Build game-review monitors by scheduling recent-review runs for target apps.
• Use it as a Steam reviews API workflow for CSV, JSON, Excel, or direct Dataset API exports.

Common workflows

• Sentiment analysis: classify positive and negative Steam reviews by language, game, or time period.
• Game launch monitoring: track recent reviews after updates, releases, discounts, or patches.
• Competitor research: compare player complaints and praise across similar games.
• Localization analysis: collect reviews by language to understand regional feedback.
• Product feedback mining: extract recurring issues, feature requests, and player language.
• Review dashboards: feed review rows into BI tools, warehouses, or spreadsheets.

What data can you collect?

Each dataset row represents one public Steam review.

Field	Description
appId	Steam app ID
appUrl	Steam app URL
recommendationId	Unique Steam review/recommendation ID
review	Review text
language	Review language
votedUp	Whether the player recommends the game
votesUp	Helpful vote count
votesFunny	Funny vote count
weightedVoteScore	Steam weighted vote score
commentCount	Number of review comments
steamPurchase	Whether the game was purchased on Steam
receivedForFree	Whether the reviewer marked it as received for free
refunded	Whether the review is associated with a refund flag
writtenDuringEarlyAccess	Early-access review flag
primarilySteamDeck	Steam Deck related flag when available
timestampCreated	Review creation date/time
timestampUpdated	Review update date/time
authorSteamId	Public author Steam ID
authorPersonaName	Public Steam persona name when returned
authorProfileUrl	Author profile URL
playtimeForeverMinutes	Total recorded playtime in minutes
playtimeAtReviewMinutes	Playtime at the time of review
lastPlayed	Last played timestamp
querySummaryTotalReviews	Total reviews reported by Steam for the query
nextCursor	Cursor that can be used for continuation
scrapedAt	Timestamp when the row was saved

Pricing

This Actor uses Apify pay-per-event pricing. The prices below come from the current Actor pricing configuration. Apify public plans map to Store discount tiers, so the table shows both the user-facing plan context and the pricing tier name. The final price shown in Apify depends on the user account plan and any custom agreement.

Event	What is charged	Price
start	One-time fee per run	$0.005

Event	What is charged	Free / no discount	Starter / Bronze	Scale / Silver	Business / Gold	Custom / Platinum	Custom / Diamond
result	Per Steam review saved to the dataset	$0.23 / 1,000	$0.2 / 1,000	$0.156 / 1,000	$0.12 / 1,000	$0.08 / 1,000	$0.056 / 1,000

Apify may also charge platform usage for compute, storage, proxies, or data transfer outside this Actor pricing. Check the Actor run and the Apify Pricing tab for the exact cost shown to your account.

Input configuration

Setting	JSON key	Use it for	Example
Steam app IDs or URLs	appIdsOrUrls	Steam app IDs or full Steam app URLs.	["730"]
Maximum reviews per app	maxReviewsPerApp	Reviews saved for each Steam app.	100
Review order/filter	filter	Steam review feed ordering.	recent
Language	language	Steam language code or all languages.	english
Review sentiment	reviewType	Positive, negative, or all reviews.	all
Purchase type	purchaseType	Steam purchase status filter.	all
Pagination cursor	cursor	Continue from a previous run.	*
Include author metadata	includeAuthor	Save public author and playtime fields.	true
Proxy configuration	proxyConfiguration	Optional Apify Proxy settings.	{"useApifyProxy":false}

Example input

{
  "appIdsOrUrls": ["730"],
  "maxReviewsPerApp": 100,
  "filter": "recent",
  "language": "english",
  "reviewType": "all",
  "purchaseType": "all",
  "cursor": "*",
  "includeAuthor": true,
  "proxyConfiguration": { "useApifyProxy": false }
}

Example output

{
  "appId": "730",
  "appUrl": "https://store.steampowered.com/app/730/",
  "recommendationId": "123456789",
  "review": "Great competitive game with a strong community.",
  "language": "english",
  "votedUp": true,
  "votesUp": 12,
  "votesFunny": 0,
  "weightedVoteScore": 0.72,
  "steamPurchase": true,
  "playtimeAtReviewMinutes": 2400,
  "authorProfileUrl": "https://steamcommunity.com/profiles/7656119...",
  "timestampCreated": "2026-07-03T10:30:00.000Z",
  "nextCursor": "AoIIPw..."
}

Tips for best results

• Use app IDs for clean inputs: Steam app IDs such as 730 are more compact than full URLs.
• Use filter="recent" for monitoring: recent reviews are best for alerts and launch tracking.
• Set language deliberately: english is cleaner for English NLP; all is broader for global research.
• Keep author metadata on for analysis: public playtime and review counts can help segment feedback.
• Store nextCursor: use it when you need to continue collection later.

Limits and caveats

• The Actor extracts publicly visible Steam review data only.
• It does not access private profiles, private libraries, account-only data, or non-public review information.
• Some author fields may be missing when Steam does not return them.
• Steam review counts, votes, and visibility can change after scraping.

API usage

curl -X POST 'https://api.apify.com/v2/acts/fetch_cat~steam-reviews-scraper/runs?token=YOUR_APIFY_TOKEN' \
  -H 'Content-Type: application/json' \
  -d '{"appIdsOrUrls":["730"],"maxReviewsPerApp":50,"filter":"recent","language":"english"}'

MCP and AI agents

This Actor can be used through the official Apify MCP server at https://mcp.apify.com.

For a focused single-Actor tool setup, use:

https://mcp.apify.com?tools=fetch_cat/steam-reviews-scraper

Use the same JSON keys shown in the input configuration table, such as appIdsOrUrls, maxReviewsPerApp, filter, language, reviewType, purchaseType, and includeAuthor.

FAQ

Can this scrape reviews for any Steam game?

It works with public Steam app IDs and store URLs where Steam exposes public reviews.

Can I collect negative reviews only?

Yes. Set reviewType to the negative option in the input UI or API.

Can I export to CSV or Excel?

Yes. Apify datasets can be downloaded as CSV, JSON, Excel, XML, RSS, HTML, or accessed through the API.

Related scrapers

• Reddit Scraper
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• YouTube Comments Scraper
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Changelog

0.1

• Initial public release with Steam app review scraping, sentiment filters, language filters, purchase filters, author metadata, cursor continuation, and API export.

Support

If a run fails, returns no data, or a field looks wrong, open an issue from the Actor page.

Please include the Apify run ID or run URL, input JSON, one example public URL, query, or input item, what you expected, and what the dataset returned. Small reproducible inputs make parsing or site-layout issues much faster to fix.

Privacy and data handling

This Actor runs with Apify limited permissions and only processes data needed for the documented run. It uses review lookup inputs and public review results to produce the output dataset and sends requests to public Steam Reviews pages/endpoints; results are stored in Apify run storage for your account. FetchCat does not use your inputs or outputs for advertising, does not use them for model training, and does not retain them outside the Apify run except for transient support debugging when you explicitly share run details. You are responsible for using the Actor lawfully, respecting the target site's terms, and avoiding unnecessary personal or sensitive data in inputs.