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Universal Web Scraper & Data Extractor

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Universal Web Scraper & Data Extractor

Universal Web Scraper & Data Extractor

Fast AI-ready webpage extraction with structured JSON output for automation workflows, AI agents, RAG pipelines, SEO analysis, and website intelligence.

Pricing

Pay per usage

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Developer

Leoncio Jr Coronado

Leoncio Jr Coronado

Maintained by Community

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1

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3 days ago

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Fast, AI-ready webpage extraction for automation workflows, AI agents, Retrieval-Augmented Generation (RAG), website intelligence, lead generation, SEO analysis, and structured data collection.

Universal Scraper extracts structured information from webpages using a lightweight HTTP-first engine. Instead of working with raw HTML, you receive organized JSON containing metadata, headings, text, links, images, and structured data that can be used directly in automation, analytics, and AI workflows.

Designed with a modular extraction pipeline, Universal Scraper provides consistent, production-ready output that is easy to integrate into business systems, APIs, AI agents, and downstream data pipelines.


What does Universal Scraper do?

Universal Scraper combines multiple webpage extraction capabilities into a single Actor and returns the results using a predictable JSON structure.

It extracts:

  • Webpage metadata
  • Heading hierarchy (H1–H6)
  • Visible webpage text
  • Hyperlinks
  • Images
  • Structured data (JSON-LD)

Rather than parsing raw HTML yourself, you receive structured data that can be consumed immediately by automation workflows and AI applications.


Common Use Cases

Universal Scraper is suitable for a wide range of web data extraction tasks.

AI Agents

Provide AI agents with structured webpage information instead of raw HTML.

Retrieval-Augmented Generation (RAG)

Extract webpage content for indexing into vector databases and knowledge bases used by LLM applications.

Website Intelligence

Analyze webpage structure, metadata, links, and structured information for research and competitive analysis.

Lead Generation

Collect public information from company websites as part of CRM enrichment and lead qualification workflows.

SEO Analysis

Extract titles, descriptions, heading structures, canonical URLs, and links for technical SEO audits.

Research

Build structured datasets from publicly accessible webpages for reporting, analytics, and content research.

Business Automation

Feed structured webpage data into APIs, Python applications, workflow automation platforms, and business systems.


Getting Started

Using Universal Scraper requires only a few steps.

  1. Open the Actor in Apify Console.
  2. Enter one or more webpage URLs.
  3. Choose which data you want to extract.
  4. Start the Actor.
  5. Download or integrate the generated dataset.

No browser automation is required for standard webpages.


Input

Example input:

{
"start_urls": [
{
"url": "https://apify.com"
}
],
"extract_metadata": true,
"extract_headings": true,
"extract_text": true,
"extract_links": true,
"extract_images": true,
"extract_structured_data": true,
"follow_redirects": true,
"verify_ssl": true
}

Main Input Options

OptionDescription
start_urlsList of webpages to scrape
extract_metadataExtract webpage metadata
extract_headingsExtract H1–H6 headings
extract_textExtract visible webpage text
extract_linksExtract hyperlinks
extract_imagesExtract image information
extract_structured_dataExtract JSON-LD and Schema.org data
follow_redirectsFollow HTTP redirects
verify_sslVerify SSL certificates

Output

Universal Scraper returns a consistent, AI-ready JSON structure designed for automation workflows, AI applications, analytics platforms, and business systems.

Example output:

{
"url": "https://apify.com",
"resolved_url": "https://apify.com",
"title": "Apify: Full-stack web scraping and data extraction platform",
"description": "Build, deploy, and publish web scrapers, AI agents, and automation tools.",
"canonical_url": "https://apify.com/",
"language": "en",
"metadata": {
"og:type": "website",
"og:site_name": "Apify"
},
"headings": [
{
"level": "h1",
"text": "Web scraping meets AI"
}
],
"text_content": "Build reliable web scraping and automation workflows...",
"links": [
{
"url": "https://docs.apify.com",
"text": "Documentation",
"link_type": "external"
}
],
"images": [
{
"src": "/images/logo.svg",
"alt": "Apify",
"title": ""
}
],
"structured_data": [
{
"format": "json-ld",
"schema_type": "Organization",
"content": "{...}"
}
]
}

The exact output depends on the enabled extraction options and the structure of the target webpage.


Key Features

Universal Scraper is designed to provide clean, structured webpage data through a lightweight and production-oriented extraction engine.

Metadata Extraction

Extract important webpage metadata including:

  • Page title
  • Meta description
  • Canonical URL
  • Document language
  • Open Graph metadata
  • Twitter Card metadata
  • HTML meta tags

Heading Extraction

Build the complete heading hierarchy of a webpage.

Supported elements:

  • H1
  • H2
  • H3
  • H4
  • H5
  • H6

Text Extraction

Extract visible webpage text suitable for:

  • AI preprocessing
  • Knowledge bases
  • Search indexing
  • Content analysis
  • Natural Language Processing (NLP)

Collect hyperlinks and automatically classify them as:

  • Internal
  • External
  • Email
  • Telephone
  • Anchor

Image Extraction

Extract image information including:

  • Source URL
  • Alternative text
  • Title attribute

Structured Data Extraction

Extract structured information embedded in webpages, including:

  • JSON-LD
  • Schema.org data

Why Choose Universal Scraper?

Universal Scraper is designed for reliability, maintainability, and easy integration into modern automation workflows.

Consistent JSON Output

Receive predictable, structured data instead of raw HTML, reducing the need for custom parsing.

AI-Ready

Use the extracted data directly in:

  • AI Agents
  • LLM applications
  • Retrieval-Augmented Generation (RAG)
  • Knowledge bases
  • Automation workflows

Lightweight

The HTTP-first architecture provides fast extraction for standard webpages without requiring browser automation.

Modular

Independent extraction modules make it easy to configure the Actor based on the information you need.

Production-Oriented

Built with maintainability, extensibility, and predictable output as primary engineering goals.

Limitations

Universal Scraper V1 focuses on fast and reliable HTTP-based webpage extraction. To keep the extraction engine lightweight and maintainable, the current version has the following limitations:

  • JavaScript-rendered content is not supported.
  • Login-protected pages are not supported.
  • Browser automation is not included in V1.
  • Recursive website crawling is not supported.
  • Extraction quality depends on the HTML structure and accessibility of the target webpage.

These limitations are intentional design decisions that prioritize reliability, predictable output, and ease of maintenance. Future releases may expand the supported capabilities while preserving the existing output format.


Best Fit

Universal Scraper is an excellent choice for:

  • AI engineers building LLM applications
  • Automation developers
  • Data engineers
  • SEO professionals
  • Researchers and analysts
  • Growth and marketing teams
  • Business intelligence teams
  • Developers integrating webpage data into automation systems

Typical Workflows

Universal Scraper works well as a building block in larger automation pipelines.

Example workflow:

Website

Universal Scraper

Structured JSON

AI Agent / RAG Pipeline / CRM / Analytics / API

Because the output structure is predictable, downstream systems require minimal custom parsing.


Performance

Universal Scraper uses a lightweight HTTP-first architecture designed for efficient extraction of standard webpages.

Advantages include:

  • Fast execution
  • Low memory usage
  • No browser startup overhead
  • Configurable extraction modules
  • Predictable JSON output

This design makes the Actor suitable for automation workflows that require structured webpage data without the additional resource cost of browser-based scraping.


Version Roadmap

Current Release

  • HTTP-first webpage extraction
  • Metadata extraction
  • Heading extraction
  • Text extraction
  • Link extraction
  • Image extraction
  • Structured data extraction

Future Enhancements

Future releases may introduce:

  • JavaScript rendering
  • Browser automation
  • Multi-page crawling
  • Additional extractors
  • AI-assisted content extraction
  • Enhanced content normalization

The current V1 output model is intended to remain stable as new capabilities are introduced.


Support & Resources

Universal Scraper is actively maintained and designed for long-term evolution.

Resources include:

  • GitHub repository
  • Issue tracker
  • Technical documentation
  • Apify Actor page

Bug reports, feature requests, and community feedback are always welcome and help guide future development.


Why Universal Scraper?

Many web scraping tools focus on extracting only one type of information or require developers to combine multiple libraries and custom scripts.

Universal Scraper provides a unified extraction engine that returns structured, AI-ready JSON through a single, consistent workflow. This simplifies automation, reduces development time, and provides a reliable foundation for integrating webpage data into business applications and AI systems.

Whether you're building an AI agent, enriching business data, analyzing websites, or creating automated research workflows, Universal Scraper helps you move from raw HTML to structured information with minimal effort.


License

Universal Scraper is provided under the MIT License.


Feedback

Your feedback helps improve Universal Scraper.

If you discover a bug, have suggestions for new features, or would like to contribute ideas for future releases, please open an issue in the project repository.

Community feedback plays an important role in guiding future improvements while maintaining a stable and reliable extraction engine.


About This Project

Universal Scraper is developed following the LeoCor Engineering Principles:

  • Business-first software.
  • People-first design.

The project emphasizes:

  • Production-grade architecture
  • Modular engineering
  • Predictable output
  • Long-term maintainability
  • AI-ready data extraction

Thank you for using Universal Scraper.