AI-Powered Web Scraping

Wikipedia scraper

Get Wikipedia infobox data, references, and article text into a clean spreadsheet — no code, the AI does the structuring for you.
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harvard_university logobcg logoadidas logored_bull_technology logored_hat logowix logosams_club logopatagonia logocarvana logoarmis logoflywire logomit logocolliers logomonster_energy logoharvard_university logobcg logoadidas logored_bull_technology logored_hat logowix logosams_club logopatagonia logocarvana logoarmis logoflywire logomit logocolliers logomonster_energy logoharvard_university logobcg logoadidas logored_bull_technology logored_hat logowix logosams_club logopatagonia logocarvana logoarmis logoflywire logomit logocolliers logomonster_energy logoharvard_university logobcg logoadidas logored_bull_technology logored_hat logowix logosams_club logopatagonia logocarvana logoarmis logoflywire logomit logocolliers logomonster_energy logoharvard_university logobcg logoadidas logored_bull_technology logored_hat logowix logosams_club logopatagonia logocarvana logoarmis logoflywire logomit logocolliers logomonster_energy logoharvard_university logobcg logoadidas logored_bull_technology logored_hat logowix logosams_club logopatagonia logocarvana logoarmis logoflywire logomit logocolliers logomonster_energy logo

Extract Wikipedia data in two clicks

Point and extract Wikipedia data instantly

Manually copying data from Wikipedia is tedious. Thunderbit lets you grab infobox data, article text, categories, and more with zero code. Just point at the data you want, and with a second click, Thunderbit learns the fields and extracts them. No complicated setup or CSS selectors needed.

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Thunderbit adapts to wikipedia's layout changes

Wikipedia's layout always seems to be changing, breaking traditional scrapers. Thunderbit uses semantic AI to understand the meaning of the page, not just fixed selectors. This means it adapts to layout changes automatically, so you can keep scraping article text, references, and other data without constantly fixing your scraper.

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Export Wikipedia data to your tools

Stop wasting time copy-pasting data like table data and external links from Wikipedia into your spreadsheets. Thunderbit lets you export your scraped data to Google Sheets, Notion, or Airtable with a single click. It's the fastest way to get Wikipedia's 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
Wikipedia's layout changes break selectors often
Complex table structures require custom code
Pagination through categories is difficult
Inconsistent infobox formats need cleaning
PDF citations are inaccessible as data
The AI Advantage

Thunderbit

The smarter approach
Semantic AI adapts to layout changes
AI detects fields with 2-click extraction
Auto-pagination handles categories seamlessly
Auto data cleaning structures inconsistent data
Extract data from PDFs and images

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Frequently asked questions

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