# Steam Reviews Scraper - Reviews, Playtime, Votes & Ratings (`alex9080/steam-reviews-scraper`) Actor

Scrape Steam game reviews from the official store API: recommended or not, text, language, date, helpful and funny votes, playtime at review, author stats, developer responses, plus the game's overall rating summary. Search games by name, filter by sentiment, language, date and playtime.

- **URL**: https://apify.com/alex9080/steam-reviews-scraper.md
- **Developed by:** [Alex](https://apify.com/alex9080) (community)
- **Categories:** Developer tools
- **Security:** Limited permissions
- **Stats:** 3 total users, 2 monthly users, 46.7% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.20 / 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/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

### Steam Reviews Scraper

Scrape **Steam game reviews** from the official store review API: recommended or not, full text, language, date, **helpful and funny votes, playtime at review and in total**, author stats (games owned, reviews written), developer responses, Steam Deck and early access flags. Each game also gets a **rating summary row**: Steam's label ("Overwhelmingly Positive"), total, positive and negative reviews and positive %.

Built for game studios, publishers, analysts and modders: find what players hate and love, compare competitors, track review bombing, monitor new reviews after an update, or feed reviews into an LLM.

#### Features

- **Games by ID, link or name** (the first store search match is used).
- **All reviews** or the latest N, newest first, recently updated or most helpful.
- **Filters**: recommended / not recommended, language, date, minimum playtime (cut off reviews from people who barely played).
- **New reviews only** for scheduled monitoring.
- **Clean numbers**: playtime in hours, ISO dates.

#### Output

```json
{
  "type": "review",
  "appId": 413150,
  "game": "Stardew Valley",
  "recommended": false,
  "text": "Really fun at the start and incredible at the middle but ...",
  "language": "english",
  "date": "2026-09-30T09:51:36+00:00",
  "votesHelpful": 12,
  "votesFunny": 1,
  "playtimeAtReviewHours": 91.9,
  "playtimeTotalHours": 91.9,
  "authorName": "boosi",
  "authorReviews": 7,
  "steamDeck": false,
  "earlyAccess": false,
  "developerResponse": null,
  "url": "https://steamcommunity.com/profiles/76561199801545581/recommended/413150/"
}
```

Game summary row: `{"type": "game", "name": "Stardew Valley", "reviewScoreDesc": "Overwhelmingly Positive", "positivePercent": 98.5, "totalReviews": 1041735, ...}`

#### Input example

```json
{
  "games": ["Stardew Valley", "730"],
  "maxReviewsPerGame": 1000,
  "reviewType": "negative",
  "language": "english",
  "minPlaytimeHours": 10,
  "since": "2026-09-01"
}
```

#### Pricing

**$0.20 per 1,000 reviews** and **$0.001 per game summary**. No subscription.

#### Notes

Uses Steam's public review API, the same data shown on store pages. Language names follow Steam's API (`english`, `german`, `schinese`, `brazilian`, `ukrainian`, ...).

# Actor input Schema

## `games` (type: `array`):

Steam app IDs (413150), store links, or game names (the first search match is used).

## `maxReviewsPerGame` (type: `integer`):

0 = all reviews.

## `reviewType` (type: `string`):

Filter by thumbs up or down.

## `language` (type: `string`):

all, or a Steam language name: english, german, french, spanish, russian, ukrainian, schinese, brazilian, ...

## `sort` (type: `string`):

Newest first is needed for the date cut-off and new-only mode.

## `since` (type: `string`):

Skip reviews written before this date.

## `minPlaytimeHours` (type: `integer`):

Skip reviews from players with less playtime.

## `onlyNewReviews` (type: `boolean`):

For scheduled monitoring: remembers the newest review per game (in your own storage).

## `includeGameSummary` (type: `boolean`):

One row per game: Steam rating label, total, positive and negative reviews, positive %.

## Actor input object example

```json
{
  "games": [
    "Stardew Valley",
    "https://store.steampowered.com/app/730/"
  ],
  "maxReviewsPerGame": 200,
  "reviewType": "all",
  "language": "all",
  "sort": "recent",
  "onlyNewReviews": false,
  "includeGameSummary": true
}
```

# Actor output Schema

## `reviews` (type: `string`):

No description

## `games` (type: `string`):

No description

## `all` (type: `string`):

No description

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "games": [
        "Stardew Valley",
        "https://store.steampowered.com/app/730/"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("alex9080/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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "games": [
        "Stardew Valley",
        "https://store.steampowered.com/app/730/",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("alex9080/steam-reviews-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "games": [
    "Stardew Valley",
    "https://store.steampowered.com/app/730/"
  ]
}' |
apify call alex9080/steam-reviews-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,alex9080/steam-reviews-scraper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/XQK4B1jli643TThbR/builds/S0QU0Z2iAsWJbXVug/openapi.json