Skool Community Scraper – Discover Niches & Pricing

Get every community listed on Skool's discovery catalog as clean JSON rows: name, description, category, price, member count and logo. Built for creators researching a niche before launching a community, market researchers tracking the creator-economy space, and AI agents that need Skool's public catalog without a login or a headless browser. Plain HTTPS calls to Skool's own server-rendered discovery page, with retries and a silent-failure check, so a scheduled run keeps working when the site hiccups.

What you get

• Every community as one row – name, slug, public URL, description, price (free or monthly/yearly/one-time USD), member count, logo image, and its position in Skool's own discovery order.
• Filters that match real research – any combination of Skool's discovery categories (Hobbies, Music, Money, Spirituality, Tech, Health, Sports, Self-improvement, Relationships) and a keyword search, with a hard cap on rows so the cost of a run is known up front.
• Catalog data only – no member lists, no personal profiles, no emails. Just the public discovery listing Skool itself shows to every visitor.

Sample row

One community from a default run (no filters):

{
  "id": "4e1ca14852434c0abdefff35382cdf66",
  "name": "Imperio Agéntico",
  "slug": "imperio",
  "url": "https://www.skool.com/imperio",
  "description": "Comunidad #1 de IA\nAquí ahorramos tiempo, vamos al grano y crecemos en serio con agentes, sistemas, vibe coding y automatizaciones con IA.",
  "category": null,
  "is_free": false,
  "price_usd": 59.0,
  "price_interval": "month",
  "member_count": 3991,
  "is_private": null,
  "image_url": "https://assets.skool.com/f/4e1ca14852434c0abdefff35382cdf66/aeb420cc00cc4f8dbc31660aaff02e0c7720982540fb4a47bec630575891bd78.jpg",
  "rank": 1,
  "created_at": "2024-04-09T15:26:09.355362Z",
  "updated_at": "2026-09-11T06:51:44.491754Z",
  "scraped_at": "2026-09-11T07:59:10+00:00"
}

Filters

Input	Default	What it does
categories	[]	Skool discovery category slugs, e.g. ["money", "tech"]. Empty = all categories. An unknown slug becomes a non-charged error row instead of failing the run.
query	""	Keep only communities matching this keyword (Skool's own discovery search).
maxCommunities	200	Keep this many rows after filtering.

Multiple categories run as separate scrapes and are merged, deduplicated by community id. category on a row is the filter that matched it, not an intrinsic property — Skool's discovery catalog does not tag a community's own category, only the search filter.

Pricing

Pay per event, no subscription: $1 per 1,000 communities. A default run (200 communities) costs $0.20. Set a maximum charge on the run and the Actor stops cleanly when it is reached, charging only for rows that were actually saved.

Use it from your tools

• API and SDKs – call it via the Apify API or the official Python/JavaScript clients: one call to start the run, one to fetch the dataset as JSON or CSV.
• Schedules – run it daily inside Apify and push new communities to Google Sheets, a webhook or your own storage automatically.
• n8n, Make and Zapier – trigger runs and pipe communities into a workflow through Apify's integration for each.
• AI agents and MCP – this Actor supports pay-per-event pricing, so an agent can call it mid-task and pay only per community it actually reads.

Details

• Source: Skool's public discovery page (skool.com/discovery), a server-rendered Next.js page whose __NEXT_DATA__ JSON block carries the full community list, category list and pagination state. No authentication, no proxies, no browser, no personal data.
• Pagination: 30 communities per page; the Actor pages until it reaches maxCommunities or Skool returns a short/empty page.
• No sort option: rows come in Skool's own discovery order (roughly trending/relevance); there is no way to order by members, price or age on the source, so sort the dataset yourself.
• is_private: Skool's discovery catalog does not expose a private/public flag for a community, so this column is always null; it is kept for forward compatibility if Skool adds it.
• Reliability: 429 and 5xx responses are retried with exponential backoff (5 tries), a 200 without the expected __NEXT_DATA__ block counts as a failure, and one bad category never stops the run: it becomes an error row (category, error, errorMessage) and the rest continues. A run fails only when it produced no rows and hit request errors; a filter with no matching communities is a successful, empty run.
• Run stats: the STATS record in the run's key-value store holds request and error counts per category (network, rate_limit, blocked, not_found, other).
• Speed: a default run (200 communities, 7 requests) finishes in a few seconds.
• Output: one dataset row per community with the columns above first and every raw Skool metadata field after them. The Overview table shows name, category, free/paid, price, members and URL. Export as JSON, CSV or Excel, fetch through the Apify API, or schedule runs and pipe them into Google Sheets, Make, Zapier or your own code.

Not affiliated with Skool.