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from $1.00 / 1,000 article fetcheds

Wikipedia Research Intelligence — Topic Maps & Research Briefs

Turn a Wikipedia query into structured topic understanding: the primary concept, what matters, what to read first, the people and organizations around it, and the gaps. Returns a deterministic research brief, topic map, and scored, classified results across 15 languages.

Pricing

from $1.00 / 1,000 article fetcheds

Rating

0.0

(0)

Developer

Ryan Clinton

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Bookmarked

Total users

Monthly active users

11 days ago

Last modified

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Developer tools

You can access the Wikipedia Research Intelligence — Topic Maps & Research Briefs 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 Integrations settings in Apify Console.

Python

JavaScript

CLI

OpenAPI

HTTP

MCP

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          "language": {
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              "it",
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              "ko",
              "pl",
              "sv",
              "vi"
            ],
            "type": "string",
            "description": "Wikipedia language code (e.g., en, de, fr, es, ja, zh, ru, pt, it, ar)",
            "default": "en"
          },
          "includeSummary": {
            "title": "Include Article Summary",
            "type": "boolean",
            "description": "Fetch article summary/extract for each result (slower but richer data)",
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          },
          "maxResults": {
            "title": "Max Results",
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          },
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              "full"
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            "default": "standard"
          },
          "intent": {
            "title": "Search Intent",
            "enum": [
              "general",
              "research",
              "recent",
              "overview"
            ],
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            "description": "Reweights the quality score for your use case (same five signals, different lens). 'general' is balanced. 'research' favours depth and structure (long, well-referenced articles). 'recent' favours recently-edited articles. 'overview' favours the most relevant results for a quick answer.",
            "default": "general"
          },
          "includeRelated": {
            "title": "Include Related Articles",
            "type": "boolean",
            "description": "Fetch the top related articles for each result (Wikipedia's own related-pages graph). Adds one extra request per article, so it is slower; useful for knowledge-graph building and topic exploration.",
            "default": false
          },
          "compareLanguages": {
            "title": "Compare Language Coverage",
            "maxItems": 20,
            "type": "array",
            "description": "Optional list of additional Wikipedia language codes (e.g. de, fr, ja) to compare how broadly this topic is covered. When set, the run summary record includes a per-language hit count and a coverage score. Does not change the main results, which still come from the primary Language above.",
            "items": {
              "type": "string"
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          },
          "expandTopic": {
            "title": "Build Topic Map (research surface)",
            "type": "boolean",
            "description": "Generate a research-surface topic map for the query: core concepts plus the people, organizations, related fields, and related concepts around it (classified deterministically from Wikidata entity types and the related-article graph). Emits one extra 'topic-map' record. Adds a few requests; useful for research and knowledge-graph workflows.",
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          },
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            "type": "boolean",
            "description": "Emit a single 'research-brief' record that synthesises the run into a 5-minute understanding of the topic: primary concept, executive summary, what matters, reading order, key people/organizations, and gaps. Built deterministically from the run's own data (no LLM, no extra calls). On by default; turn off if you only want raw result rows.",
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Wikipedia Knowledge Graph Search & Research Briefs 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 Research Intelligence — Topic Maps & Research Briefs 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 Research Intelligence — Topic Maps & Research Briefs API in Python

Wikipedia Research Intelligence — Topic Maps & Research Briefs API in JavaScript

Wikipedia Research Intelligence — Topic Maps & Research Briefs API through CLI

Wikipedia Research Intelligence — Topic Maps & Research Briefs API

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