🔎 Hugging Face Spaces Scraper - AI App Data

Scrape Hugging Face Spaces pages and extract AI app names, URLs, creators, descriptions and machine-learning app metadata. Export to JSON/CSV/Excel, run on a schedule, call via API, or connect to Make, Zapier or n8n.

What is the Hugging Face Spaces Scraper?

The Hugging Face Spaces Scraper turns public AI apps pages into structured rows that are easy to filter, enrich, deduplicate and send into a CRM, spreadsheet, dashboard, data warehouse or monitoring workflow. It is designed for the same workflows that make marketplace, jobs, SaaS, app-directory and lead-generation actors valuable on Apify: finding targets, tracking categories, comparing competitors, building prospect lists and keeping a repeatable dataset fresh.

Instead of manually opening directory pages and copying names one at a time, paste one or more source URLs and let the actor collect the public listing data. The actor uses direct HTTP requests and structured-page extraction, so it stays lightweight and cost-effective. Defaults are intentionally small and reliable for Apify health checks, while maxResults lets you expand the run when you need more records.

What data does it extract?

• title - listing, app, course, job, software, template or integration name
• url - absolute URL to the listing when available
• description - public listing text, snippet, card text or structured description
• company - company, vendor, publisher or organization when exposed by the source
• kind - high-level source type such as apps, jobs, templates or courses
• source - actor/source identifier for downstream joins
• source_url - final page URL fetched after redirects
• input_url - URL you provided in the actor input
• raw - structured JSON object when the source exposes JSON data

Input

Field	Type	Description
searchUrls	array	Source directory, search or category URLs to scrape.
maxResults	integer	Maximum rows to return per input URL. Keep this small for tests and larger for production runs.

Example input

{
  "searchUrls": ["https://huggingface.co/spaces"],
  "maxResults": 25
}

Output

{
  "source": "huggingface-spaces-scraper",
  "kind": "AI apps",
  "index": 1,
  "title": "Example listing title",
  "company": "Example company",
  "url": "https://example.com/listing",
  "description": "Public listing text extracted from the page.",
  "input_url": "https://huggingface.co/spaces",
  "source_url": "https://huggingface.co/spaces"
}

Use cases

💼 B2B lead generation - collect public app, software, company, course or job listings that can become account lists, enrichment targets or outbound segments.

📊 Market research - compare categories, vendors, templates, integrations and marketplaces over time without rebuilding a custom crawler for every run.

🔎 Competitive intelligence - monitor new listings, content changes, app launches, integration directories and category pages on a schedule.

⚙️ Workflow automation - send fresh directory rows to Google Sheets, Airtable, Notion, HubSpot, Salesforce, Make, Zapier, n8n or your own API.

Production tips

For best results, start with the default input and confirm the first run returns the fields you need. Then widen the source URLs, category pages or search pages and raise maxResults gradually. This keeps the run predictable, avoids noisy datasets and makes it easier to compare changes between scheduled runs.

The actor is designed for repeatable business workflows rather than one-off copy and paste work. Use a saved task when you need the same source checked daily or weekly. Add a webhook when you want each finished dataset to flow into Make, Zapier, n8n, Slack, Google Sheets, Airtable, BigQuery or your own backend. The output fields stay stable so downstream automations can depend on title, url, description, company, source_url and input_url.

When using the data for lead generation or market research, deduplicate by url first, then enrich the remaining rows with your own CRM fields, tags, owner assignment, notes or scoring rules. For monitoring use cases, store each run separately and compare the current dataset with the previous one to find newly added listings, removed listings and changed descriptions.

Data quality notes

This scraper reads public pages and public JSON/structured data when the source exposes it. Some directories use mixed layouts: featured cards, category links, sponsored placements and normal organic listings can appear on the same page. The actor keeps a conservative extraction strategy so it returns useful rows while avoiding low-value navigation links where possible.

Every run records both the original input_url and the final source_url, which helps when a website redirects a category page, localizes content, or changes pagination. Keep those fields when exporting to a warehouse or spreadsheet; they make debugging and deduplication much easier later.

The default result limit is intentionally small so Apify health checks finish quickly and reliably. For larger collection jobs, run a small sample first, inspect the dataset, then increase maxResults and schedule the actor only after the output matches your workflow.

Why use this actor?

You can always write a custom script for one page, but maintaining dozens of small scripts is where teams lose time. This actor gives you a packaged Apify workflow: hosted execution, scheduling, logs, datasets, API access, exports, webhooks and pay-per-result billing in one place. That makes it practical for ongoing competitive tracking, prospect list building and category monitoring without maintaining servers.

FAQ

Does this actor need a login? No. It is built for public pages and does not require a username, password or private session.

Can I scrape multiple URLs? Yes. Add multiple searchUrls and the actor will process each one in the same run.

Can I increase the number of results? Yes. Raise maxResults when you need more rows. For quick tests, keep it low.

Does it use a browser? No. The actor uses direct HTTP requests and structured extraction, which keeps it faster and cheaper than browser automation.

What if the website changes layout? The actor combines structured JSON discovery, JSON-LD parsing and semantic listing extraction. If a source changes heavily, rerun with a small test first.

Is this legal? This actor extracts publicly available information. You are responsible for using the data lawfully and respecting applicable privacy, database, copyright, GDPR, CAN-SPAM and platform rules.

Can I schedule it? Yes. Use Apify schedules to refresh a marketplace, job search, template page or directory every hour, day or week.

Can I export to CSV or Excel? Yes. Apify datasets support JSON, CSV, Excel, XML and API access.

Can I use it for lead scoring? Yes. The rows can be enriched with contact extractors, website checks, traffic data, CRM fields or your own scoring model.

Why does it return fewer rows than the page visually shows? Some sites render extra items only in the browser or after scroll. This actor prioritizes reliable public data available in the initial response.

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