Wikipedia Scraper

Search Wikipedia or look up exact article titles and get back clean, structured JSON — full plain-text article content, intro summary, categories, lead image, Wikidata ID and monthly pageview trends. Works in any language edition. No account, no API key. Perfect for research, building RAG and AI training datasets, content analysis and tracking topic popularity over time.

Features

• 🔎 Search + exact titles — combine searchTerms (which pull matching articles) with exact titles; results are deduplicated by title.
• 🌍 Any language — set language to any Wikipedia edition code (en, es, de, fr, ja, …).
• 📄 Full plain text — toggle fullText for the complete article as clean plain text, or just the intro summary when off.
• 📈 Pageview trends — flip includePageviews to attach the last 6 months of monthly pageviews plus a pageviewsTotal.
• 🏷️ Rich metadata — visible categories, lead image URL, Wikidata ID, page ID, word count and last-modified timestamp on every record.
• ✂️ Clean snippets — search snippets are stripped of HTML and decoded from entities into readable text.
• 📊 Scales per term — take up to 500 articles from each search term with automatic pagination and retries.

What you get

Each dataset row is one article:

{
  "title": "Machine learning",
  "pageId": 233488,
  "url": "https://en.wikipedia.org/wiki/Machine_learning",
  "language": "en",
  "summary": "Machine learning (ML) is a field of study in artificial intelligence concerned with...",
  "text": "Machine learning (ML) is a field of study in artificial intelligence...\n\nHistory...",
  "wordCount": 9231,
  "categories": ["Machine learning", "Cybernetics", "Learning"],
  "imageUrl": "https://upload.wikimedia.org/wikipedia/commons/.../example.svg",
  "wikidataId": "Q2539",
  "lastModified": "2024-11-20T14:03:12Z",
  "searchSnippet": "Machine learning is a field of study in artificial intelligence...",
  "pageviews": [
    { "month": "202502", "views": 412034 },
    { "month": "202503", "views": 398115 }
  ],
  "pageviewsTotal": 2410882
}

Output schema

Input

{
  "searchTerms": ["quantum computing", "climate change"],
  "titles": ["Alan Turing", "Python (programming language)"],
  "language": "en",
  "maxResultsPerSearch": 20,
  "fullText": true,
  "includePageviews": true
}

Use cases

• Build clean, plain-text article corpora for RAG pipelines and AI training datasets.
• Track topic popularity over time using monthly pageview trends.
• Enrich entities with Wikidata IDs, categories and lead images.
• Compile multilingual reference content by running the same titles across language editions.

Pricing

Pay-per-event: you're billed a small amount per run and per item scraped — you only pay for what you get. See the Pricing tab for current rates.

FAQ

Do I need a Wikipedia account or API key? No. The actor uses Wikipedia's public MediaWiki APIs and the Wikimedia pageviews API — no account, login or API key.

How many articles can I scrape per run? Each search term can return up to 500 articles (maxResultsPerSearch), with automatic pagination and retries. You can also add any number of exact titles, and results are deduplicated by title.

Can I scrape non-English Wikipedia? Yes. Set language to any Wikipedia edition code (en, es, de, fr, ja, …), and run the same titles across editions for multilingual corpora.

What's the output format? Structured JSON — one record per article with title, url, summary, full plain-text text, wordCount, categories, imageUrl, wikidataId and optional monthly pageviews. Export as JSON, CSV, Excel or via the API.

Can I get full article text and pageview trends? Yes. Toggle fullText for the complete cleaned plain text (or just the intro summary when off), and set includePageviews to attach the last 6 months of monthly pageviews plus a pageviewsTotal.

Can I connect this to other apps and services? The Wikipedia Scraper can be connected with almost any cloud service or web app thanks to integrations on the Apify platform. It works with Make, Zapier, Slack, Airbyte, GitHub, Google Drive and many more, plus the Apify API, JavaScript/Python clients and MCP. Or use webhooks to trigger an action whenever a run finishes.

Building research or RAG datasets? Combine this with our other reference and developer-data scrapers:

• Stack Overflow & Stack Exchange Scraper — questions by tag or search across Stack Exchange sites.
• Hacker News Scraper — stories, comments and Ask/Show HN by keyword and filters.
• GitHub Scraper — repositories and user profiles with stars, topics, licenses and leads.
• npm Package Scraper — search and look up npm packages with metadata, dependencies and downloads.

Notes

This Actor uses Wikipedia's public MediaWiki APIs and the Wikimedia pageviews API, returning that content as-is over openly available pages with no login required. Article text is available under Wikipedia's own licensing (typically CC BY-SA); check and comply with those terms for reuse. This is an independent tool and is not affiliated with, endorsed by, or sponsored by Wikipedia or the Wikimedia Foundation.

You pay only for what the run returns. Set a maximum cost per run and it stops cleanly at that limit.