AI-Powered Web Scraping

Wikipedia scraper

Turn Wikipedia infobox data, references, and article text into a clean, structured spreadsheet in 2 clicks — export to Excel, Google Sheets, or Notion instantly, no code required.

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Extract Wikipedia data in two clicks

Point and extract Wikipedia data instantly

Manually copying data from Wikipedia is tedious and error-prone. Thunderbit lets you extract infobox data, article text, categories, and more with zero code. Just point at the data you want, and with a second click, Thunderbit identifies the fields and pulls them into a clean table. No complicated setup or CSS selectors needed.

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Thunderbit adapts to Wikipedia's layout changes

Wikipedia's layout is always evolving, and traditional scrapers break every time it does. Thunderbit uses semantic AI to understand the meaning of a page, not just fixed selectors. That means it adapts to layout changes automatically, so you can keep extracting article text, references, and structured data without constantly patching your scraper.

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Export Wikipedia data to your tools

Stop wasting time copy-pasting table data and external links from Wikipedia into your spreadsheets. Thunderbit lets you export extracted data to Excel, Google Sheets, Notion, or Airtable with a single click. It's the fastest way to get Wikipedia's structured data into the tools you already use.

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Struggling to scrape Wikipedia effectively?

See why Thunderbit outperforms traditional scrapers for Wikipedia data extraction.

Traditional scrapers

The old way of doing things
Layout changes frequently break fixed selectors
Complex table structures require custom code
Category pagination is difficult to handle
Inconsistent infobox formats require manual cleanup
PDF citations and images are inaccessible as data
The AI Advantage

Thunderbit

The smarter approach
Semantic AI adapts automatically to layout changes
AI detects fields — extract anything in 2 clicks
Auto-pagination navigates categories seamlessly
Automatic data cleaning structures inconsistent content
Extract data from PDFs and embedded images

Don't just take our word for it

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Frequently asked questions

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View All Use Cases

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