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Wikipedia Scraper icon

Full Wikipedia Article Text Scraper (Plain Text)

Need the complete body of Wikipedia articles? This task returns full plain-text content by title, ready for NLP, summarization, and text analysis.

Run this use case nowRun on Apify →

How it works

  1. 1
    Open it on Apify

    Hit Run on Apify — it opens the tool in the cloud, no install.

  2. 2
    Set the inputs

    Adjust searchQuery, pageTitles, fullText (sensible defaults are pre-filled).

  3. 3
    Click Run

    The tool runs on Apify’s cloud and collects the data for you.

  4. 4
    Export the results

    Download as JSON, CSV or Excel, or pipe straight into your app, Google Sheets, or an AI agent.

Inputs

FieldWhat it doesType
searchQueryKeywords to search Wikipedia for (e.g. "machine learning"). Returns matching pages with snippet, word count, and URL. Leave empty if you instead provide exact Pstring
pageTitlesExact Wikipedia article titles to fetch full data for (plain-text extract, thumbnail, categories, URL). Batched 50 at a time. Use this OR a search query.array
fullTextOnly applies in Page titles mode. When on, returns the whole article as plain text instead of just the intro paragraph(s).boolean
languageWikipedia language edition code, e.g. en, fr, de, es, ja. Picks the host {lang}.wikipedia.org.string
maxItemsMaximum number of pages to return. In search mode the actor paginates until it reaches this. In page-titles mode it caps how many titles are fetched.integer
notionConnectorOptional. Write each page as a page into your Notion when the run finishes. Authorize a Notion connector once in Settings → API & Integrations → MCP connectors,string
notionParentIdOptional. The Notion data source ID of the database to write into (only used if a Notion connector is set). Leave empty to create the pages privately in your wostring

What you get

A structured dataset — each result includes fields like:

modepageidsizesnippettimestamptitleurlwordcount

Export every run as JSON, CSV or Excel, or send it to your app, a database, Google Sheets, or an AI agent.

More use cases for Wikipedia Scraper

Wikipedia Search API: Find Pages by Keyword

Search Wikipedia by keyword and rank matching pages by relevance, with snippets and word counts so researchers can decide what to read first.

Bulk Wikipedia Fetch: Get Page Data by Title

Pass up to 50 page titles and get each Wikipedia entry's intro, thumbnail, and categories back as clean JSON for datasets and enrichment.