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Wikipedia Scraper [$0.7💰/1k] | RAG & AI Training

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Extract structured data from Wikipedia articles — infoboxes, sections, tables and full text. Build knowledge graphs, RAG pipelines and AI training datasets from the world's largest encyclopedia.

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from $0.67 / 1,000 results

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Developer

Ahmed Jasarevic

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a day ago

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You can access the Wikipedia Scraper [$0.7💰/1k] | RAG & AI Training programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in API & Integrations in Apify Console.

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JavaScript

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OpenAPI

HTTP

MCP

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          "maxSectionTextLength": {
            "title": "Max Text Length per Section",
            "minimum": 0,
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            "default": 50000
          },
          "extractTables": {
            "title": "Extract Tables",
            "type": "boolean",
            "description": "Whether to extract wikitext tables from the article content.",
            "default": true
          },
          "extractWikitext": {
            "title": "Extract Wikitext",
            "type": "boolean",
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          },
          "maxInfoboxFields": {
            "title": "Max Infobox Fields",
            "minimum": 0,
            "type": "integer",
            "description": "Maximum number of infobox fields to extract (0 = all).",
            "default": 50
          },
          "maxSectionDepth": {
            "title": "Max Section Depth",
            "minimum": 1,
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            "type": "integer",
            "description": "Maximum section heading depth to extract (1 = h2 only, 2 = h2+h3, etc.).",
            "default": 3
          },
          "maxTables": {
            "title": "Max Tables",
            "minimum": 0,
            "type": "integer",
            "description": "Maximum number of tables to extract (0 = all).",
            "default": 20
          },
          "useApiForInfobox": {
            "title": "Use Wikipedia API for Infobox",
            "type": "boolean",
            "description": "Use Wikipedia REST API to parse infobox from wikitext (more accurate). Disable to use HTML parsing only.",
            "default": true
          },
          "useApiForSections": {
            "title": "Use Wikipedia API for Sections",
            "type": "boolean",
            "description": "Use Wikipedia REST API to get section hierarchy from TOC (more accurate). Disable to use HTML parsing only.",
            "default": true
          },
          "language": {
            "title": "Wikipedia Language",
            "pattern": "^[a-z]{2,3}(-[a-z]{2,3})?$",
            "type": "string",
            "description": "Wikipedia language edition code (e.g., 'en', 'de', 'fr', 'es', 'ja', 'zh').",
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          },
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            "title": "Max Requests per Crawl",
            "minimum": 0,
            "type": "integer",
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          },
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Wikipedia Scraper — Structured Data & RAG OpenAPI definition

OpenAPI is a standard for designing and describing RESTful APIs, allowing developers to define API structure, endpoints, and data formats in a machine-readable way. It simplifies API development, integration, and documentation.

OpenAPI is effective when used with AI agents and GPTs by standardizing how these systems interact with various APIs, for reliable integrations and efficient communication.

By defining machine-readable API specifications, OpenAPI allows AI models like GPTs to understand and use varied data sources, improving accuracy. This accelerates development, reduces errors, and provides context-aware responses, making OpenAPI a core component for AI applications.

You can download the OpenAPI definitions for Wikipedia Scraper [$0.7💰/1k] | RAG & AI Training from the options below:

OpenAPI.json

If you’d like to learn more about how OpenAPI powers GPTs, read our blog post.

You can also check out our other API clients:

Wikipedia Scraper [$0.7💰/1k] | RAG & AI Training API in Python

Wikipedia Scraper [$0.7💰/1k] | RAG & AI Training API in JavaScript

Wikipedia Scraper [$0.7💰/1k] | RAG & AI Training API through CLI

Wikipedia Scraper [$0.7💰/1k] | RAG & AI Training API

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