Wikipedia To Markdown
Under maintenancePricing
from $50.00 / 1,000 article scrapes
Go to Apify Store

Wikipedia To Markdown
Under maintenanceConvert any Wikipedia article into clean, distraction-free Markdown. Strips infoboxes, references, navboxes, and edit links, leaving only the article content ready for AI/LLM consumption
Pricing
from $50.00 / 1,000 article scrapes
Rating
0.0
(0)
Developer
Extreme Scrapes
Maintained by CommunityActor stats
0
Bookmarked
1
Total users
0
Monthly active users
5 days ago
Last modified
Categories
Share
Wikipedia to Clean Markdown
Convert any Wikipedia article into clean, distraction-free Markdown. Strips infoboxes, references, navboxes, and edit links — leaving only the article content ready for AI/LLM consumption.
Features
- Accept titles or URLs — just type "Artificial intelligence" or paste the full URL
- Multilingual support — works with any Wikipedia language edition (en, de, fr, es, ja, etc.)
- Clean output — removes infoboxes, references, navboxes, edit sections, and sidebar noise
- Batch processing — extract multiple articles in a single run
- AI-optimized — structured Markdown ready for LLMs, RAG, and embeddings
How It Works
- Provide article titles or Wikipedia URLs as input.
- Optionally set the language code (default: English).
- The Actor normalizes inputs, fetches articles, and strips noise.
- Clean Markdown is stored in the Apify dataset.
Input
{"startUrls": [{ "url": "Artificial intelligence" },{ "url": "https://en.wikipedia.org/wiki/Machine_learning" }],"language": "en"}
Output
{"url": "Artificial intelligence","normalizedUrl": "https://en.wikipedia.org/wiki/Artificial_intelligence","markdown": "# Artificial intelligence\n\nArtificial intelligence (AI) is..."}
Use Cases
- Build knowledge bases from Wikipedia content
- Create AI training datasets from encyclopedia articles
- Feed factual content into RAG pipelines
- Generate study materials from Wikipedia
Keywords
wikipedia scraper, wikipedia to markdown, wiki extractor, wikipedia parser, wikipedia API
Pricing
$20 per 1,000 article extractions.