# Wikipedia Article Scraper (`crawlerbros/wikipedia-scraper`) Actor Extract structured data from Wikipedia articles. Get summaries, categories, images, metadata, and descriptions using Wikipedia's official API. Supports 300+ languages. - **URL**: https://apify.com/crawlerbros/wikipedia-scraper.md - **Developed by:** [Crawler Bros](https://apify.com/crawlerbros) (community) - **Categories:** Other, Developer tools, SEO tools - **Stats:** 1 total users, 0 monthly users, 50.0% runs succeeded, 11 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing from $0.50 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Wikipedia Article Scraper Extract structured data from Wikipedia articles using the official MediaWiki API. Get article summaries, categories, images, metadata, and descriptions. Supports 300+ languages. ### Features - Extract article titles, summaries, and descriptions - Get categories, images, and thumbnails - Support for 300+ Wikipedia languages - Two modes: scrape by URL or search by keyword - Uses official Wikipedia REST + MediaWiki APIs - No proxy or cookies required - Lightweight HTTP-only (no browser) - Proper rate limiting and User-Agent identification ### Input | Field | Type | Default | Description | |-------|------|---------|-------------| | `articleUrls` | Array | — | Wikipedia article URLs to scrape | | `searchQueries` | Array | — | Search terms to find articles | | `maxArticlesPerQuery` | Integer | 5 | Max articles per search query (1-50) | | `language` | String | "en" | Wikipedia language code | #### Example: Scrape by URL ```json { "articleUrls": [ "https://en.wikipedia.org/wiki/Python_(programming_language)", "https://en.wikipedia.org/wiki/Artificial_intelligence" ] } ```` #### Example: Search by Keyword ```json { "searchQueries": ["machine learning", "quantum computing"], "maxArticlesPerQuery": 3, "language": "en" } ``` ### Output | Field | Type | Description | |-------|------|-------------| | `title` | String | Article title | | `url` | String | Full Wikipedia URL | | `summary` | String | Lead section extract (first few paragraphs) | | `description` | String | Wikidata short description | | `categories` | Array | Article categories | | `thumbnail` | Object | Thumbnail image with source, width, height | | `images` | Array | Image filenames from the article | | `lastModified` | String | Last edit timestamp | | `language` | String | Language code | | `pageId` | Integer | Wikipedia page ID | | `scrapedAt` | String | ISO timestamp when scraped | ### Use Cases - **Research** — collect structured article data for academic or business research - **Content enrichment** — augment your database with Wikipedia descriptions and metadata - **Knowledge graphs** — build knowledge bases from Wikipedia's categorized data - **Education** — gather article summaries for educational content - **SEO** — analyze Wikipedia's coverage of topics in your niche - **Data science** — use Wikipedia data for NLP training and analysis ### FAQ #### Is a proxy required? No. Wikipedia's API is freely accessible. No proxy, cookies, or authentication needed. #### What languages are supported? All 300+ Wikipedia language editions. Set the `language` parameter to any valid code: en, fr, de, es, ja, zh, ru, pt, it, ar, ko, nl, pl, etc. #### Are there rate limits? Wikipedia asks for polite access with proper User-Agent headers. The scraper includes built-in delays (0.3-0.5s between requests) to respect Wikipedia's guidelines. #### Can I scrape article content (full text)? This scraper extracts the lead section summary. For full article text, the summary field contains a clean text extract of the opening paragraphs which is suitable for most use cases. # Actor input Schema ## `articleUrls` (type: `array`): Wikipedia article URLs to scrape. ## `searchQueries` (type: `array`): Search terms to find Wikipedia articles. ## `maxArticlesPerQuery` (type: `integer`): Maximum articles per search query. ## `language` (type: `string`): Wikipedia language code (e.g., 'en', 'fr', 'de', 'es', 'ja'). ## Actor input object example ```json { "articleUrls": [ "https://en.wikipedia.org/wiki/Python_(programming_language)" ], "maxArticlesPerQuery": 5, "language": "en" } ``` # Actor output Schema ## `articles` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "articleUrls": [ "https://en.wikipedia.org/wiki/Python_(programming_language)" ], "maxArticlesPerQuery": 5, "language": "en" }; // Run the Actor and wait for it to finish const run = await client.actor("crawlerbros/wikipedia-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "articleUrls": ["https://en.wikipedia.org/wiki/Python_(programming_language)"], "maxArticlesPerQuery": 5, "language": "en", } # Run the Actor and wait for it to finish run = client.actor("crawlerbros/wikipedia-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "articleUrls": [ "https://en.wikipedia.org/wiki/Python_(programming_language)" ], "maxArticlesPerQuery": 5, "language": "en" }' | apify call crawlerbros/wikipedia-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=crawlerbros/wikipedia-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Wikipedia Article Scraper", "description": "Extract structured data from Wikipedia articles. Get summaries, categories, images, metadata, and descriptions using Wikipedia's official API. Supports 300+ languages.", "version": "1.0", "x-build-id": "lw1bPPJLsuh4kv0iP" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/crawlerbros~wikipedia-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-crawlerbros-wikipedia-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/crawlerbros~wikipedia-scraper/runs": { "post": { "operationId": "runs-sync-crawlerbros-wikipedia-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/crawlerbros~wikipedia-scraper/run-sync": { "post": { "operationId": "run-sync-crawlerbros-wikipedia-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "articleUrls": { "title": "Article URLs", "type": "array", "description": "Wikipedia article URLs to scrape.", "items": { "type": "string" } }, "searchQueries": { "title": "Search Queries", "type": "array", "description": "Search terms to find Wikipedia articles.", "items": { "type": "string" } }, "maxArticlesPerQuery": { "title": "Max Articles Per Query", "minimum": 1, "maximum": 50, "type": "integer", "description": "Maximum articles per search query.", "default": 5 }, "language": { "title": "Language", "type": "string", "description": "Wikipedia language code (e.g., 'en', 'fr', 'de', 'es', 'ja').", "default": "en" } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```