Wikidata MCP server

Wikidata — Structured Knowledge Graph

Wikidata is the free, structured-data sister of Wikipedia. ~110 million items (people, places, works, concepts) with machine-readable properties and relationships. The closest thing the open web has to a universal knowledge graph. Free, no auth, supports SPARQL queries.

Part of Pipeworx — an MCP gateway connecting AI agents to 1679+ live data sources.

Why this matters for AI agents

For entity disambiguation, structured facts about anything notable, or graph traversal ("what books did this author write that won prizes?"), Wikidata is the canonical open source. Pair with Wikipedia (prose) and OpenAlex (academic specifics) for full open-knowledge coverage.

Common flows:

• Entity lookup. "Who is Paul McCartney?" → Q2599 with structured facts (birth date, nationality, occupation, band memberships).
• Property query. "What's the population of France?" → Q142, property P1082 (population), with references and timestamps.
• Disambiguation. "Paris" → Q90 (capital of France), Q830149 (Paris, Texas), Q3296 (Paris, Greek mythology). Wikidata's structured types resolve which "Paris" the agent is asking about.
• Graph traversal. SPARQL: "All Nobel laureates in Physics born in Italy" → joinable across structured properties.

Tools

Reading labels in another language

searchentities, getentity, getentities and getwikidatafacts all take language. It is passed straight to the API's own languages param, so a single code ("ka") or a comma/pipe-joined list ("ka,ru,en") both work, and a list returns every requested language's label, description and aliases side by side in one upstream call** — the shape you need to decide whether two records in different languages are the same entity. Omit it and you get English, exactly as before.

Two fields, and the difference matters:

what Wikidata actually has**. Ask for a language the entity has no label in and the key is simply absent — that absence is the honest answer, and it is how you detect a translation gap.

• labels / descriptions / aliasesbylanguage are keyed by language and contain **only

requested language is missing. So get_entity({id:"Q162887", language:"zu"}) returns label: "Enguri HPP" with an empty labels map: there is no Zulu label, and you can tell.

• label / description are the single best value, and they fall back to English when the

getwikidatafacts localizes both halves — property names and their values — so {id:"Q162887", language:"ka"} comes back with Georgian keys (ქვეყანა → საქართველო), not English keys with Georgian values.

Shortened. The full README is on GitHub.