Apify Store Intel Scraper (Actors + Inputs/Outputs)

Scrape the Apify Store catalog and optionally extract each actor’s input/output schema fields so you can compare competitors on what they actually accept and return — not just their titles and pricing.

No browser automation required.

Why you’d pick this over other “store scrapers”

Most Apify Store scrapers stop at “list actors + some stats”. This one is built for market/competitive intelligence:

• Schema intelligence (unique): extract inputFields + outputFields so you can see how actors are designed.
• Counts mode: get nbHits + facets (categories, pricing model, managedBy, …) for quick market snapshots.
• Output shaping: return only the fields/paths you need (and rename them) to keep datasets clean.
• Stable IDs + normalized records: easier downstream joins and deduping.

If you only need generic “70+ fields”, there are other actors for that (e.g. “Smart Apify Actor Scraper”). If you need inputs/outputs for competitive analysis, this actor is the fast path.

Quick start

1. Pick operation: "search" (dataset output) or operation: "counts" (summary output).
2. Add filters (keywords, category, pricing, ratings, freshness).
3. Enable include_schemas when you want input/output fields.

Inputs (plain language)

Core

• operation: search or counts
• query: keywords to search (items are OR; multiple words in one item are AND; wrap in quotes for an exact phrase)
• search_on: where to search (name, title, description, username, readme)
• limit: max number of actors to return (free plan capped at 100)
• sort: relevance, popular, newest, update

Filters

• username: only these developer usernames
• manager: APIFY, COMMUNITY, or ALL
• category: filter by categories
• modified_hours: only actors modified in the last N hours
• featured: only featured actors
• rating: minimum average rating
• reviews: minimum review count
• bookmarks: minimum bookmark count
• users_count: period for users filter (total, week, month, threemonth)
• users_min, users_max: users bounds for the selected period
• price_model: pricing model(s) to include
• price_min, price_max: price bounds (USD)

Schema intelligence

• include_schemas: fetch input schema + output field lists (extra requests, slower)

Output shaping

• fields: whitelist output fields (empty = default set)
• select_fields: project output items to specific paths (dot notation + array indexes)
• rename_fields: rename selected paths in the output

Performance controls

• hitsPerPage: pagination size for the search API
• maxChargedResults: soft cap to stop early (0 disables)

Monetization (recommended vs. competition)

Goal: cheap for market scans, paid when you extract the “premium” intel (schemas).

Pay-per-event:

• apify-actor-start → $0.05 per run
• incl-schemas → +$0.10 per run (only when include_schemas=true)

Why this works:

• Competing catalog scrapers tend to monetize by “more fields” or “per item”. We monetize the value add (schemas) while keeping baseline scans affordable.
• A low start fee makes it easy to adopt, then schema mode captures the willingness-to-pay of teams doing competitive research.

(We can later add an optional scaling event like “per 1k actors” if we see heavy users pulling full-catalog daily.)

Example: Search with schema intelligence

Input:

{
  "operation": "search",
  "query": ["scraper", "tiktok"],
  "manager": "COMMUNITY",
  "category": ["SOCIAL_MEDIA"],
  "sort": "popular",
  "limit": 5,
  "include_schemas": true
}

Output item (sample):

{
  "id": "aYG0l9s7dbB7j3gbS",
  "title": "Website Content Crawler",
  "username": "apify",
  "categories": ["AI", "DEVELOPER_TOOLS"],
  "currentPricingInfo": { "pricingModel": "FREE" },
  "inputFields": ["startUrls", "maxPagesPerCrawl"],
  "outputFields": ["url", "title", "text"],
  "sourceUrl": "https://apify.com/apify/website-content-crawler"
}

Example: Counts (market snapshot)

Input:

{
  "operation": "counts",
  "category": ["SOCIAL_MEDIA"],
  "manager": "COMMUNITY"
}

Output (verify-report excerpt):

{
  "counts": {
    "nbHits": 2603,
    "facets": {
      "categories": { "AI": 242, "SOCIAL_MEDIA": 1099 },
      "managedBy": { "APIFY": 78, "COMMUNITY": 2525 },
      "currentPricingInfo.pricingModel": { "FREE": 527, "PAY_PER_EVENT": 410 }
    }
  }
}

Select only what you need

When select_fields is provided, each output item is projected to only those paths. Paths use dot notation for objects and numeric segments for array indexes (for example currentPricingInfo.pricingModel, categories.0). Missing paths are omitted. If multiple paths resolve to the same key, the last one wins.

Input:

{
  "operation": "search",
  "select_fields": [
    "id",
    "title",
    "username",
    "currentPricingInfo.pricingModel",
    "categories.0"
  ],
  "rename_fields": {
    "currentPricingInfo.pricingModel": "pricingModel",
    "categories.0": "firstCategory"
  }
}

Output item (sample):

{
  "id": "aYG0l9s7dbB7j3gbS",
  "title": "Website Content Crawler",
  "username": "apify",
  "pricingModel": "FREE",
  "firstCategory": "AI"
}

Output notes

• In search mode, results are saved to the dataset.
• In counts mode, no items are saved; instead a summary is stored under verify-report.
• After every run, a short verify-report is saved for validation.

Disclaimer

This actor provides informational data from the Apify Store. Schemas/fields are extracted as-is and may change at any time. You are responsible for how you use this information.