AI Web Scraper — Any URL to JSON by Prompt ✅ No Code

AI Web Scraper — Any URL to JSON by Prompt ✅ No Code

Extract structured data from any URL with a natural-language prompt — describe what you want, get it back as clean data. No code, no CSS selectors, no LLM API key. Add an optional JSON Schema when you need an exact output shape. Powered by the Neuralverge API. You only pay for successful extractions — misses are free. Export to JSON, CSV or Excel.

Ideal for one-off and repeatable extraction, monitoring, enrichment, research, and feeding clean data to AI agents (MCP-ready).

✨ Why this Actor

• 💸 Pay only for successful extractions — if a page returns no content (or times out), the row is skipped and never billed. Misses are free.
• 🗣️ Just describe what you want — a natural-language prompt instead of code or selectors. Nothing to maintain when a site changes its markup.
• 🔑 No LLM API key, no login — the model and fetching run on the Neuralverge backend. You don't bring an OpenAI/Gemini key.
• 🎯 Optional JSON Schema — pass one to force an exact structured shape; omit it to get a clean markdown result. Geo-routing (countryCode) built in. MCP-ready for AI agents.

🔧 How it works

1. Provide a URL and an instruction (e.g. "Extract company name, website, industry, founded year, specialties"). Optionally add a JSON Schema for an exact shape.
2. Run the Actor. Fetching + AI extraction run on the Neuralverge backend.
3. Get one dataset row. With a schema, the fields land as top-level columns; without one, the result is a markdown summary in human. The full response is under raw.

If a URL returns no content (or an upstream error like a 504), it's logged and skipped without charge — you're not billed for that run.

Input

One URL per run.

Field	Type	Notes
url	string	The page URL to extract from.
instructions	string	Natural-language description of what to extract.
extractSchema	object	Optional JSON Schema for an exact output shape.
countryCode	string	Two-letter geo-routing code (advanced, default us).
finalizerModel	string	Extraction model (advanced).

{
  "url": "https://www.linkedin.com/company/ibm",
  "instructions": "Extract company name, website, industry, founded year, specialties"
}

What you'll receive

• Without a schema — a clean markdown result in human (the extracted facts), plus query, scrapedAt and the full response under raw.
• With a JSON Schema — the schema's fields spread to top-level columns, alongside human and raw.

Example output (real run)

A real dataset row from https://www.linkedin.com/company/ibm with the prompt above and no schema — shown in full. With no schema the backend returns machine: null, so there are no structured columns; the extracted facts come back as text in human, and the complete API response is kept under raw.

{
  "query": "https://www.linkedin.com/company/ibm",
  "scrapedAt": "2026-07-18T12:00:00.000Z",
  "human": "Company Name: IBM\nWebsite: http://www.ibm.com\nIndustry: IT Services and IT Consulting\nFounded Year: N/A\nSpecialties:\n- Analytics\n- Commerce\n- Research\n- Financing\n- Consulting\n- IT infrastructure\n- Experience Design\n- Cloud\n- Security\n- Internet of Things\n- Mobile\n- Cognitive\n- Technology support\n- Watson\n- Industry solutions\n- Resiliency services\n- Systems services",
  "raw": {
    "kind": "extract",
    "url": "https://www.linkedin.com/company/ibm",
    "used_url": "https://www.linkedin.com/company/ibm",
    "instructions": "Extract company name, website, industry, founded year, specialties",
    "settings": {
      "has_schema": false,
      "country_code": "us"
    },
    "human": "Company Name: IBM\nWebsite: http://www.ibm.com\nIndustry: IT Services and IT Consulting\nFounded Year: N/A\nSpecialties:\n- Analytics\n- Commerce\n- Research\n- Financing\n- Consulting\n- IT infrastructure\n- Experience Design\n- Cloud\n- Security\n- Internet of Things\n- Mobile\n- Cognitive\n- Technology support\n- Watson\n- Industry solutions\n- Resiliency services\n- Systems services",
    "machine": null,
    "total_points": 5
  }
}

Genuine result from a live run (no schema, total_points: 5). Note Founded Year: N/A and the full 17-item specialties list come straight from the page. Pass a JSON Schema to get company_name, website, industry, founded_year, specialties as separate top-level columns instead (then machine is populated and its fields are spread into the row); the full API response is always kept under raw.

Pricing

Pay per result — $0.005 per successful extraction ($5 per 1,000). You pay only for rows returned — empty or failed extractions are free.

Event	Price
Actor start	Free
Successful extraction (per dataset row)	$0.005

URLs that return no content are not billed. Pricing is on top of your Apify platform usage.

Integrations & API

Results are stored in a standard Apify dataset — export as CSV, JSON, XML or Excel, or fetch on demand through the Apify API. The Actor also plugs into Apify's integrations (Make, Zapier, n8n, webhooks) and can be called from any MCP client to give an AI agent a general-purpose web-extraction tool.

FAQ

Do I need an OpenAI/Gemini or Crunchbase-style API key? No. The model and fetching run on the Neuralverge backend — you bring nothing but a URL and a prompt.

Do I have to write selectors or code? No. Describe what you want in plain language.

When should I use a JSON Schema? When you need a guaranteed structure (fixed field names/types) for a database or pipeline. Otherwise the markdown result in human is enough.

Am I charged if extraction fails? No. You're billed only for rows returned to the dataset; empty results and upstream errors are logged and skipped.

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Disclaimer: This Actor is an independent tool. You are responsible for ensuring you have the right to extract from the URLs you submit and for complying with each site's terms and applicable law. All trademarks are property of their respective owners.