Wikidata Scraper - Knowledge Graph Entity Data

Search Wikidata - the free knowledge graph behind Wikipedia - or resolve Q-ids directly, and get clean structured rows for every entity: label, description, aliases, instance-of, country, industry, founders, CEO, headquarters, official website, coordinates, ISIN, revenue and the Wikipedia link. Built for entity resolution and data enrichment. No key, no browser.

What you get per entity

Field	Meaning
id / label / description / aliases	Q-id, name, one-line description and alternate names
instanceOf / subclassOf / dataType	What kind of thing it is
country / headquartersLocation / coordinates	Location data
industry / employees / founders / ceo / revenue	Company facts where present
officialWebsite / officialName / legalForm / isin / stockExchange	Corporate identifiers
ownedBy / parentOrg / partOf / inception	Ownership and history
claimPropertyCount / wikipediaUrl / wikidataUrl	Richness signal and canonical links

Input

{ "searchQueries": ["Tesla", "Marie Curie"], "language": "en", "maxItemsPerQuery": 10 }

• Search terms - names or terms, one per line; each resolves to matching entities.
• Q-ids - exact entity lookups (e.g. Q42). Language - label/description language (falls back to English).
• Import from a file - paste a list, or link a public .txt/.csv, a Google Sheet/Drive link, or an Apify key-value-store record (terms and Q-ids auto-detected). Output fields trim every record.

Leave everything empty and the run returns a small free sample so you can see the shape first.

Reliability

Reads the official Wikidata API (wbsearchentities + wbgetentities) - public, keyless, no anti-bot, batched 50 entities per request. A search that returns nothing bills $0.

Honest limits

• Claims are a curated high-value subset (instance-of, country, industry, founders, CEO, website, coordinates, ISIN and more), not every one of Wikidata's thousands of properties - claimPropertyCount tells you how many the entity has in total, and wikidataUrl links the full record.
• A field is present only when the entity has that claim - most items are not companies, so corporate fields (CEO, ISIN, revenue) are null for people, places and concepts. That is the data's shape.
• Coverage and freshness follow Wikidata's community edits.

Pricing

$0.001 per entity on the FREE tier (tiered pricing lowers it with volume). Only entities actually saved are billed; an empty search costs nothing.

Output views

• Entities - Q-id, label, description, instance-of, country, website and Wikipedia link.

Use with AI assistants (MCP)

Available through the Apify MCP server - an agent can resolve a company name to a canonical Q-id, enrich a list with country/industry/website, or disambiguate entities in one call.

Agent-ready: autonomous payments (x402 & Skyfire)

This actor is agent-ready - AI agents can discover it, run it, and pay for it autonomously, with no Apify account and no human in the loop. It uses pay-per-event pricing and limited permissions, so it qualifies for Apify's agentic-payment standards:

• x402 - an open, HTTP-native payment protocol. Agents pay per run in USDC on the Base network directly through the Apify MCP server - no account, no API key.
• Skyfire - agent-to-service payments for fully autonomous AI-agent workflows.

Building an AI agent, MCP tool, or autonomous data pipeline? This scraper is ready to plug in and pay as it goes.