Wikipedia Category Scraper — Articles for RAG & AI
Pricing
from $3.00 / 1,000 wikipedia articles
Wikipedia Category Scraper — Articles for RAG & AI
Extract Wikipedia articles from any category with titles, URLs, extracts, page IDs, categories, and metadata. A fast MediaWiki API actor for building RAG datasets, knowledge bases, research corpora, and AI training data.
Extract clean, structured JSON from MediaWiki API. This Actor is built for RAG datasets, knowledge bases, research corpora, AI training data.
What you can do with it
- Rag datasets
- Knowledge bases
- Research corpora
- Ai training data
Features
- Extract all pages in a Wikipedia category
- Titles, URLs, page IDs, extracts, categories, and metadata
- Fast MediaWiki API extraction
- Great for knowledge-base and RAG pipelines
Example input
Example output
Output
Results are saved to the default Apify dataset as structured JSON. The actor includes an output schema so results are easy to preview, export, and consume from API clients.
Pricing
This Actor is configured for pay-per-result monetization using Apify's pay-per-event model. Users pay for dataset items/results rather than a large fixed upfront fee.
Common use cases
- AI/RAG dataset creation
- Market research and competitive intelligence
- Trend monitoring
- Data enrichment pipelines
- Scheduled data extraction
Keywords
wikipedia category scraper, MediaWiki API, RAG dataset, knowledge base data, AI training data
Notes
This Actor focuses on practical structured data extraction with clean defaults and low overhead. For large runs, start with a small maxItems value, verify the output, then scale up.
