Scrape Apify Store — All Actors with Stats & Pricing

What is Apify Store Scraper — Extract All Actor Listings?

Apify Store Scraper is an Apify Actor for analysts, developers, and automation workflows that need structured catalog data from the Apify Store. It accepts category filters, sort order, pricing filters, maintainer scope, an item cap, and optional detail enrichment. Each output record represents one Apify Store actor listing, so one record means one listing with fields such as the actor slug, title, URL, description, developer info, categories, pricing model, entry price, pricing events, user stats, ratings, bookmarks, deprecation status, and scrape timestamp. The result is a dataset you can use for catalog analysis, workflow routing, reporting, and Apify MCP-driven lookups.

Best fit and connected workflows

This Actor fits workflows that start with Apify Store discovery and end with structured catalog analysis. It routes well when you want to:

• review actors by category, pricing model, or maintainer scope
• compare listings by popularity, total users, ratings, and pricing structure
• build a dataset for internal search, reporting, or downstream enrichment
• use Apify MCP to ask about the store and receive structured results
• monitor store listings with repeatable runs and dataset exports

This Actor also works well when a broad store question needs to become a shortlist of actor listings and their metadata.

Practical scenario

Mina, an automation specialist, starts with a request to find paid Developer Tools actors maintained by Apify and ordered by popularity. She sets categoryNames to ["Developer Tools"], pricingModels to PAID, and maintainedBy to apify. The returned records include full_name, url, developer_username, pricing_model, entry_price_usd, and rating_average. Mina uses those fields to shortlist listings for a team review, then opens the matched store pages to compare the README summary and pricing details.

Input fields

Field	Type	Default	Purpose
categoryNames	array	[]	Filter by one or more Apify Store categories. Leave empty for all categories.
sortBy	string	popularity	Sort order: popularity, newest, lastUpdate, totalUsers, or relevance.
pricingModels	string	All	Filter by pricing: All, FREE, or PAID.
maintainedBy	string	All Developers	Narrow results to all developers or apify.
maxItems	integer	0	Cap the number of actors to scrape. 0 returns the full catalog.
enrichDetails	boolean	true	Add detail-page fields such as publish date, last modified, version, build number, defaults, SEO text, and README summary.
detailConcurrency	integer	10	Set parallel detail fetches per batch, from 1 to 20.

Focused JSON input example

{
  "categoryNames": ["Developer Tools", "Automation"],
  "sortBy": "popularity",
  "pricingModels": "PAID",
  "maintainedBy": "apify",
  "maxItems": 25,
  "enrichDetails": true,
  "detailConcurrency": 8
}

Output fields

Field	Type	Purpose
actor_id	string or null	Internal Apify identifier for the actor.
title	string or null	Store display title.
full_name	string or null	Actor slug in khadinakbar/apify-store-scraper-name format.
url	string or null	Direct Apify Store URL.
description	string or null	Short store description.
developer_username	string or null	Developer username.
developer_url	string or null	Developer profile URL.
is_official_apify	boolean	Indicates whether the actor is built and maintained by Apify.
categories	array	Categories assigned in the store.
pricing_model	string or null	Pricing model, such as PAY_PER_EVENT.
is_free	boolean or null	Free or paid flag.
entry_price_usd	number or null	Lowest pricing tier value, if available.
pricing_events	array	Pricing event objects with title, description, and price.
total_users	number or null	All-time unique users.
monthly_users	number or null	Unique users in the last 30 days.
success_rate	number or null	Successful-execution percentage.
bookmarks	number or null	Saved/bookmarked count.
rating_average	number or null	Average star rating.
rating_count	number or null	Total number of ratings.
picture_url	string or null	Icon image URL.
is_deprecated	boolean	Deprecation flag from the developer.
scraped_at	string	ISO 8601 timestamp for the record.

Illustrative dataset record

{
  "actor_id": "h5vZMp0iNGoVB58jy",
  "title": "Google Maps Scraper",
  "full_name": "compass/crawler-google-places",
  "url": "https://apify.com/compass/crawler-google-places",
  "description": "Extract data from thousands of Google Maps locations...",
  "developer_username": "compass",
  "developer_url": "https://apify.com/compass",
  "is_official_apify": false,
  "categories": ["Lead Generation", "Travel"],
  "pricing_model": "PAY_PER_EVENT",
  "is_free": false,
  "entry_price_usd": 0.004,
  "pricing_events": [
    {
      "title": "Scraped place",
      "description": "Cost per place scraped",
      "price_usd": 0.004
    }
  ],
  "total_users": 329581,
  "monthly_users": 20178,
  "success_rate": 95.1,
  "bookmarks": 3631,
  "rating_average": 4.76,
  "rating_count": 1063,
  "picture_url": "https://images.apifyusercontent.com/...",
  "is_deprecated": false,
  "scraped_at": "2026-03-28T12:00:00.000Z"
}

How it works

This Actor uses the Apify Store API as its source and paginates through the catalog to collect listing data. When enrichDetails is enabled, it fetches each actor's detail page to add publish date, last modified time, current version, build number, memory and timeout defaults, SEO title, SEO description, and README summary. You can lower enrichDetails for a faster shallow scan or keep it enabled for richer dataset records. detailConcurrency controls how many detail fetches run in parallel per batch.

Pricing

This Actor uses Apify's Pay per event pricing model plus standard Apify platform usage. The record schema includes pricing_model, is_free, entry_price_usd, and pricing_events, so you can review how listings are priced in the store.

Open the live Pricing tab in the Apify Console for current event pricing and platform usage details. For example, if a execution processes one hundred scraped actor records, the event-based charge pattern shown in the Pricing tab applies to those records, and Apify platform usage applies separately for the run.

Use with AI agents (MCP)

This Actor is usable through Apify MCP as a structured tool for Apify Store catalog lookups. An agent can pass filters, retrieve listing records, and use the returned dataset for analysis, routing, and follow-up actions.

Tool description: Apify Store catalog scraper for listing metadata, pricing fields, ratings, user stats, developer information, and optional detail enrichment.

Exact Actor identity: khadinakbar/apify-store-scraper

Find all free AI actors from the Apify Store, sort them by popularity, and return the fields needed to compare titles, pricing, ratings, and developer info.

The dataset returns one record per Apify Store actor listing. full_name is the slug for API and CLI usage, actor_id is the internal identifier, and scraped_at shows when each record was captured. When enrichDetails is enabled, the dataset can include richer listing context from the detail page. Pagination is handled by the Actor, while cost follows the selected pay-per-event pattern shown in the live Pricing tab and the Apify platform usage that applies to the run.

Apify API example

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({
  token: process.env.APIFY_TOKEN,
});

const run = await client.actor('khadinakbar/apify-store-scraper').call({
  categoryNames: ['Developer Tools'],
  sortBy: 'popularity',
  pricingModels: 'All',
  maintainedBy: 'All Developers',
  maxItems: 10,
  enrichDetails: true,
  detailConcurrency: 5,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(`Read ${items.length} dataset items`);
console.log(items);

Best results and outcome guidance

Start with a narrow category filter when you already know the part of the store you want to analyze. Use sortBy: "popularity" for broad discovery, sortBy: "newest" for recent listings, and sortBy: "totalUsers" when comparing established actors. Keep enrichDetails enabled when your next step depends on publish date, version, build number, or README summary. Lower maxItems for a quick sample and raise it when you need a broader catalog slice.

Continue the workflow

• Then use Apple App Store All-in-One Scraper to extend Apify Store Scraper — Extract All Actor Listings with a neighboring software ecosystem research source when the brief calls for App Store data.
• Then use Shopify App Store Scraper to extend Apify Store Scraper — Extract All Actor Listings with a neighboring software ecosystem research source when the brief calls for Shopify App Store data.

Design note

I found that the dataset contract separates overview fields from full-detail fields, and the full view includes bookmarks, is_deprecated, and scraped_at alongside the core listing metadata. That makes it practical to document both lightweight discovery and richer detail enrichment from the same Actor.

FAQ

How should I route a category-based research task?
Use categoryNames with one or more store categories, then read full_name, title, and pricing_model from the dataset.

How do I find actors maintained by Apify?
Set maintainedBy to apify and keep sortBy aligned with your review goal, such as popularity or totalUsers.

How do I compare free and paid listings?
Set pricingModels to All, FREE, or PAID, then inspect is_free, entry_price_usd, and pricing_events.

Which field should an API workflow use to call a specific actor later?
Use full_name for CLI and API calls, and actor_id when you need the internal Apify identifier.

Can an AI agent use this Actor for Apify Store lookups?
Yes. Through Apify MCP, the agent can query this Actor, read structured dataset items, and use the returned metadata for routing or analysis.

Responsible use

Use the results for catalog research, workflow routing, analysis, and store discovery. Review returned pricing and listing metadata directly in the Apify Store before taking actions that depend on current store details.