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Wikipedia APIWikipedia.org

Search Wikipedia articles, retrieve full text and metadata, and browse category trees via 3 structured endpoints. JSON responses with pageid, extract, and categories.

Endpoints
3
Updated
14d ago
Try it
Number of results to return (1-50).
Search query string.
Pagination offset for fetching next page of results.
api.parse.bot/scraper/cabed3f6-f0a2-4ce6-ab14-897da89a04db/<endpoint>
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curl -X GET 'https://api.parse.bot/scraper/cabed3f6-f0a2-4ce6-ab14-897da89a04db/search_articles?limit=5&query=Python+%28programming+language%29' \
  -H 'X-API-Key: $PARSE_API_KEY'
All endpoints · 3 totalclick to expand

Search Wikipedia articles by keyword query. Returns matching articles with titles, snippets, word counts, and timestamps. Supports pagination via offset.

Input
ParamTypeDescription
limitintegerNumber of results to return (1-50).
querystringSearch query string.
offsetintegerPagination offset for fetching next page of results.
Response
{
  "type": "object",
  "fields": {
    "query": "search query string that was used",
    "offset": "current pagination offset",
    "articles": "array of article summaries with pageid, title, snippet, size, wordcount, and timestamp",
    "total_hits": "total number of matching articles",
    "next_offset": "offset for the next page of results, or null if no more pages"
  },
  "sample": {
    "data": {
      "query": "artificial intelligence",
      "offset": 0,
      "articles": [
        {
          "size": 269229,
          "title": "Artificial intelligence",
          "pageid": 1164,
          "snippet": "Artificial intelligence (AI) is the capability of computational systems to perform tasks typically associated with human intelligence, such as learning",
          "timestamp": "2026-05-02T09:37:23Z",
          "wordcount": 26715
        }
      ],
      "total_hits": 27451,
      "next_offset": 5
    },
    "status": "success"
  }
}

About the Wikipedia API

The Wikipedia API provides 3 endpoints that cover article search, detailed content retrieval, and category browsing across the entirety of English Wikipedia. search_articles returns ranked results with snippets, word counts, and timestamps. get_article_details returns the full article extract, categories, revision ID, and byte length by either title or page ID. get_category_members lets you walk the category tree with typed pagination.

Endpoints and What They Return

The search_articles endpoint accepts a query string and returns an articles array where each item includes pageid, title, snippet, size, wordcount, and timestamp. The total_hits field tells you how many results exist across all pages, and next_offset provides a direct value to pass into the offset parameter for the next page. Results are limited to a maximum of 50 per call.

Article Details

get_article_details requires either a title (e.g., 'Artificial intelligence') or a pageid (e.g., '21721040'). By default it returns the introductory extract only; set full_extract to 'true' to retrieve the complete article text. The response includes url, length in bytes, language, last_revision_id, content_model, and a categories array listing every category the article belongs to.

Browsing Category Trees

get_category_members accepts a category name without the Category: prefix and returns up to 50 members per call. The type parameter controls what is returned: 'page' for articles, 'subcat' for subcategories, or 'file' for media files. Each member object contains pageid, title, and namespace. Pagination is token-based: the next_continue field from one response is passed as the continue parameter in the next call, and is null when no further results exist.

Common use cases
  • Build a knowledge base ingestion pipeline using full_extract to pull complete article text by title.
  • Populate autocomplete or search suggestions using search_articles with snippet and title fields.
  • Map topic hierarchies by recursively calling get_category_members with type: 'subcat'.
  • Cross-reference article freshness using the timestamp from search results and last_revision_id from article details.
  • Resolve ambiguous entity names to canonical Wikipedia pageid values for use in downstream data pipelines.
  • Enumerate all articles within a subject area (e.g., 'Machine learning') by paginating through get_category_members with type: 'page'.
  • Collect structured metadata — word count, byte length, language, content model — for corpus analysis.
Pricing & limitsSee full pricing →
TierPriceCredits/monthRate limit
Free$0/mo1005 req/min
Hobby$30/mo1,00020 req/min
Developer$100/mo5,000250 req/min

One credit = one API call regardless of which marketplace API you call. Exceeding the rate limit returns a 429 response. Authenticate with the X-API-Key header.

Frequently asked questions
Does Wikipedia have an official developer API?+
Yes. Wikipedia exposes the MediaWiki Action API at https://www.mediawiki.org/wiki/API:Main_page, as well as the REST-based Wikimedia REST API at https://en.wikipedia.org/api/rest_v1/. Both are publicly documented and free to use directly.
What does `get_article_details` return by default versus with `full_extract: 'true'`?+
By default, the extract field contains only the introductory section of the article. Setting full_extract to 'true' replaces that with the complete article text. All other response fields — url, title, length, pageid, language, categories, content_model, and last_revision_id — are returned regardless of that parameter.
Does the API cover languages other than English?+
The language field is returned in get_article_details responses, but the current endpoints are scoped to English Wikipedia. Non-English Wikipedia editions are not covered. You can fork this API on Parse and revise it to target a different language edition.
Can I retrieve article revision history or diff data?+
Not currently. The API exposes only the last_revision_id for the current article state; full revision history and diff data are not available through these endpoints. You can fork this API on Parse and revise it to add a revision-history endpoint.
How does pagination work across the three endpoints, and are the mechanisms consistent?+
search_articles uses an integer offset that you read from next_offset in each response. get_category_members uses an opaque string token: read next_continue from one response and pass it as the continue parameter in the next. Both return a null sentinel when no further pages exist. get_article_details is a single-record lookup and has no pagination.
Page content last updated . Spec covers 3 endpoints from Wikipedia.org.
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