AI & RAG Clean Markdown + JSON-LD + Tables Web Extractor avatar

AI & RAG Clean Markdown + JSON-LD + Tables Web Extractor

Pricing

$3.00 / 1,000 extracted url / domain results

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AI & RAG Clean Markdown + JSON-LD + Tables Web Extractor

AI & RAG Clean Markdown + JSON-LD + Tables Web Extractor

Converts any list of URLs into clean, token-efficient Markdown, extracts JSON-LD/Schema.org data, HTML tables as JSON, and page metadata. Built for AI Agents, RAG pipelines, and LLM knowledge bases.

Pricing

$3.00 / 1,000 extracted url / domain results

Rating

0.0

(0)

Developer

Albert

Albert

Maintained by Community

Actor stats

0

Bookmarked

2

Total users

1

Monthly active users

a day ago

Last modified

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Convert any list of web URLs into clean, token-efficient Markdown, structured HTML tables (as JSON), and embedded Schema.org / JSON-LD metadata in seconds.

Designed specifically for AI Agents, RAG Pipelines (LangChain / LlamaIndex), n8n / Make automations, and LLM Knowledge Bases.


Why Use This Extractor Instead of Raw HTML Scraping?

  1. Saves 70%–85% on LLM Token Costs: Automatically strips <nav>, <footer>, <script>, <style>, ads, and cookie banners before converting to Markdown.
  2. Preserves Structured Tables as JSON: Financial tables, pricing comparisons, and technical specs are extracted into clean JSON arrays alongside the Markdown.
  3. Automatic Schema.org / JSON-LD Extraction: Captures product prices, ratings, FAQs, and article metadata embedded in <script type="application/ld+json">.
  4. Built-in Token Estimator: Every output record includes estimated_tokens and word_count so your RAG pipeline can chunk documents safely.

Example Input

{
"urls": [
"https://example.com/pricing",
"https://example.com/documentation"
],
"includeTables": true,
"includeSchemaOrg": true,
"maxCharsPerUrl": 50000
}

Example Output

{
"url": "https://example.com/benchmark",
"status_code": 200,
"title": "Hetzner vs AWS Cost Report 2026",
"description": "Benchmark of cloud vs self-hosted servers.",
"word_count": 14,
"estimated_tokens": 19,
"tables_count": 1,
"json_ld_count": 1,
"markdown": "# Cloud vs Self-Hosting Benchmark\n\nMigrating PostgreSQL from **AWS RDS** to Docker saves up to 82%.",
"tables": [
[
["Provider", "Monthly Cost"],
["AWS RDS 16GB", "$296"],
["Hetzner Cloud 16GB", "$19"]
]
],
"json_ld": [
{
"@context": "https://schema.org",
"@type": "TechArticle",
"headline": "Cloud Cost Benchmark"
}
]
}

How to Deploy to Apify Store in 2 Minutes (Monetization Guide)

  1. Install Apify CLI once:
    npm install -g apify-cli
    apify login
  2. Push this Actor from /home/broquil/pasivo/actors/ai-rag-web-extractor:
    cd /home/broquil/pasivo/actors/ai-rag-web-extractor
    apify push
  3. In Apify Console -> Publication, enable Monetization and select Rental ($19/month with 3-day free trial) or Pay per result ($1.50 per 1,000 results).