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Wikipedia & Wikidata API
x402
Wikipedia & Wikidata API is a paid API for AI agents from agent-data.centorprat.workers.dev, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-28).
Given up to 3 entity names (companies, people, places, things), returns a structured record per entity including Wikipedia summary, Wikidata ID, key facts, image, and 30-day pageviews.
Price / call$0.01
Success—
StatusUnknown
How this service works
Pay-per-call data and tools for AI agents, $0.002-0.01 per call in USDC via x402 (Base, Polygon or Solana), no account or API key; MAX tiers ($0.05-0.25) run deeper jobs. Agent toolkit: web search, search + read top pages, any page as clean markdown with a prompt-injection check, which-x402-API-to-call recommender, seller check. Data: Google Maps places with contacts, YouTube video data and transcripts, job listings (Indeed, LinkedIn, 13 boards), Google Ads Transparency, TikTok comments, Pinterest, Airbnb, Redfin, AliExpress, app stores, live sports, website and SEO checks, Shopify store tech stacks, and onchain token / address risk checks.
Output
For each entity, the agent receives a structured record containing: a Wikipedia summary paragraph, the Wikidata entity ID (e.g. Q12345), key factual attributes (country, founded date, headquarters, CEO, website, industry), a Wikipedia image URL, and the 30-day pageview count. Failed lookups are flagged but not billed.
Example use cases
Company research enrichment pipeline
“I have a list of three companies — Stripe, Shopify, and Klarna — can you fetch their Wikipedia summaries, Wikidata IDs, founding dates, headquarters, CEOs, and 30-day pageviews so I can enrich my CRM records?”
LLM grounding for a named entity
“Before I trust this AI-generated claim about Elon Musk, can you pull his structured Wikipedia and Wikidata record — summary, key facts, and current role — so I can verify the details?”
Country fact lookup for a report
“I'm writing a report and need structured data on Germany, Japan, and Brazil — can you get me their Wikipedia summaries, Wikidata IDs, GDP info, and any other key facts available?”
Technical details
Endpoint
POSThttps://agent-data.centorprat.workers.dev/tools/wikipedia-wikidata-api?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need fast, structured encyclopedic enrichment for named entities (companies, people, places, things) without managing Wikipedia/Wikidata API credentials yourself. It is ideal for LLM grounding, knowledge graph population, CRM enrichment, and fact verification tasks where you need a single consolidated record with summary, Wikidata ID, key facts, image, and popularity signal in one call. Prefer it over raw Wikipedia/Wikidata APIs when you want keyless bulk access up to 3 entities per call and pay-per-use pricing with no failed-lookup charges.
Side effects
- Entity not found on Wikipedia or Wikidata — record returned with failure flag, not billed
- Ambiguous entity name resolving to wrong Wikipedia article
- Non-English Wikipedia editions may have less complete Wikidata fact coverage
- Exceeding 3 entities per call returns a validation error
- Rate limiting or payment failure on x402 protocol
- Very new entities may lack Wikidata facts or pageview history
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| entity | string | A single entity name (company, person, place, thing). Example: OpenAI |
| entities | array | An array of names, e.g. ["OpenAI","Spain","Bitcoin"]. Billed per entity. |
| language | string | Wikipedia language edition (ISO code). Default en. |
Output
Schema · Response
{
"type": "json",
"example": {
"items": [
{
"url": "https://en.wikipedia.org/wiki/OpenAI",
"facts": {
"ceo": {
"qid": "Q7407093",
"label": "Sam Altman"
},
"country": {
"qid": "Q30",
"label": "United States"
},
"founder": {
"qid": "Q7407093",
"label": "Sam Altman"
},
"industry": {
"qid": "Q11660",
"label": "artificial intelligence"
},
"employees": {
"value": 4500
},
"inception": {
"value": "2015-12-11"
},
"instanceOf": {
"qid": "Q6881511",
"label": "enterprise"
},
"revenueUsd": {
"value": 44485
},
"headquarters": {
"qid": "Q62",
"label": "San Francisco"
},
"officialWebsite": {
"value": "https://openai.com/"
}
},
"query": "OpenAI",
"title": "OpenAI",
"extract": "OpenAI is an American artificial intelligence (AI) public benefit corporation (PBC) headquartered in San Francisco, California, led by CEO Sam Altman. It develops \"frontier\" generative AI models, particularly its generative pre-trained transformer (GPT) series of large language models.",
"sources": [
"wikipedia.org",
"wikidata.org",
"wikimedia.org (pageviews)"
],
"hasFacts": true,
"resolved": true,
"thumbnail": "https://thumb.wikimedia.org/wikipedia/commons/thumb/a/a7/1515_Third_Street.jpg/330px-1515_Third_Street.jpg?utm_source=en.wikipedia.org&utm_campaign=api&utm_content=thumbnail",
"wikidataId": "Q21708200",
"coordinates": null,
"description": "American artificial intelligence company",
"isDisambiguation": false,
"monthlyPageviews": 348151
}
]
}
}Tags
x402
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