# Steam Reviews — Fast Public API (`quartz_apple_dnx/steam-reviews-fast-api`) Actor

Export public Steam game reviews with review text, recommendation, playtime, votes, purchase flags, timestamps, and reliable cursor pagination. No login, browser, proxy, or API key.

- **URL**: https://apify.com/quartz\_apple\_dnx/steam-reviews-fast-api.md
- **Developed by:** [Austin DeMoss](https://apify.com/quartz_apple_dnx) (community)
- **Categories:** Games, E-commerce, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$0.10 / 1,000 steam 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 — Fast Public API

Export public Steam game reviews through Steam's Store review endpoint with reliable cursor pagination.

No Steam login, API key, browser, or proxy is required.

### What it does

- accepts numeric Steam App IDs or store URLs;
- returns review text, recommendation, language, timestamps, votes and comments;
- returns public author/playtime fields Steam includes with each review;
- supports Steam language, recommendation, purchase-type, and feed-order filters;
- follows Steam's cursor instead of assuming a short page means the feed ended;
- deduplicates by game + recommendation ID;
- caps per-game and total output;
- preserves the exact source URL used for every accepted row.

### Important pagination behavior

Steam can return fewer than 100 reviews on an intermediate page even when more reviews exist. This Actor does **not** stop merely because a page is short. It stops only when the source returns no review rows, the cursor stops advancing, a configured result cap is reached, or a source request fails.

### Example input

```json
{
  "games": ["730", "https://store.steampowered.com/app/570/Dota_2/"],
  "language": "english",
  "filterBy": "recent",
  "reviewType": "all",
  "purchaseType": "all",
  "maxReviews": 1000
}
```

### Output

Each row includes Steam's public review ID, text, language, recommendation flag, created/updated timestamps, votes, purchase/free/early-access flags, public author statistics and playtime, the App ID, exact source URL, and capture time.

`RUN_SUMMARY` contains per-game request counts, source failures, duplicate counts, native query-summary fields, and the reason pagination stopped.

### Pricing

Pay per unique review saved. Duplicates and empty pages are not billed.

### Limits

- This is a public review exporter, not a Steam account or library tool.
- Steam can change fields, filtering semantics, cursors, or rate limits.
- `recommended` is Steam's own review recommendation flag; this Actor does not infer sentiment.
- Historical completeness depends on Steam's public endpoint and the configured caps.

# Actor input Schema

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

One to 25 numeric Steam App IDs or store.steampowered.com app URLs.

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

Steam review language code such as english, spanish, german, schinese, or all.

## `filterBy` (type: `string`):

Steam review feed ordering.

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

Return all, positive/recommended, or negative/not-recommended reviews.

## `purchaseType` (type: `string`):

Filter to all reviews, Steam purchases, or non-Steam key activations.

## `dayRange` (type: `integer`):

Steam day\_range parameter used by recent/updated feeds.

## `maxReviews` (type: `integer`):

Hard cap on unique review rows saved across all games.

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

Per-game cap before moving to the next game.

## `requestDelayMs` (type: `integer`):

Polite delay between page requests for the same game.

## `timeoutSecs` (type: `integer`):

Maximum seconds allowed per Steam Store request.

## Actor input object example

```json
{
  "games": [
    "730"
  ],
  "language": "english",
  "filterBy": "recent",
  "reviewType": "all",
  "purchaseType": "all",
  "dayRange": 365,
  "maxReviews": 1000,
  "maxReviewsPerGame": 5000,
  "requestDelayMs": 400,
  "timeoutSecs": 15
}
```

# Actor output Schema

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

No description

## `summary` (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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("quartz_apple_dnx/steam-reviews-fast-api").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 = {}

# Run the Actor and wait for it to finish
run = client.actor("quartz_apple_dnx/steam-reviews-fast-api").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 '{}' |
apify call quartz_apple_dnx/steam-reviews-fast-api --silent --output-dataset

```

## MCP server setup

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

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/zxXoK3FPJeg25saKm/builds/bNMz4hSM7MBisNjIG/openapi.json