mcpbeat

Wikidata MCP Server

io.github.cyanheads/wikidata-mcp-server
answering

Wikidata MCP Server is answering right now. Last checked 4 min ago. 84 installs a week from npm. It exposes 7 tools. Last commit 30 Jul 2026.

Search and fetch Wikidata entities, execute SPARQL queries, and resolve external identifiers.

Installs per day peak 288 · avg 35 · -43% w/w
a month agotoday
Uptime history 39 hours of history · worst hour 75%
39 hours agonow
100.0%
Uptime 24h
91 of 91 checks
7
Tools
read from the server
391 ms
Response time
average over 24h
84
Installs / week
npm and PyPI

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 4 min ago.

run in your terminal
claude mcp add wikidata-mcp-server --transport http https://wikidata.caseyjhand.com/mcp
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "wikidata-mcp-server": {
      "url": "https://wikidata.caseyjhand.com/mcp"
    }
  }
}
~/.codex/config.toml
[mcp_servers.wikidata-mcp-server]
url = "https://wikidata.caseyjhand.com/mcp"
.cursor/mcp.json
{
  "mcpServers": {
    "wikidata-mcp-server": {
      "url": "https://wikidata.caseyjhand.com/mcp"
    }
  }
}
.vscode/mcp.json
{
  "mcpServers": {
    "wikidata-mcp-server": {
      "url": "https://wikidata.caseyjhand.com/mcp"
    }
  }
}

Available tools 7

Read directly from the server with tools/list, grouped by what they act on. If a tool disappears, we record the date.

wikidata
wikidata_get_entity
Fetch a Wikidata entity (item or property) by QID or PID. The fields parameter narrows the upstream fetch, not just the response — asking for labels alone costs a fraction of the whole entity, so name the fields you need. Omit fields for all data; a well-connected item is large enough to overflow, and an oversized entity returns kind: "outline" — the field categories with their byte sizes — instead of the data. Follow its retrieval_notice literally rather than picking from sections yourself — it names a fields set already measured to fit, since category sizes are additive and requesting them all would overflow again; for a category too large to deliver whole (statements or sitelinks on a major item) it names the sibling tool that can narrow it. Q-IDs (e.g. Q76) fetch items; P-IDs (e.g. P31) fetch properties from the correct endpoint automatically. Use wikidata_get_statements for deep claim traversal with label resolution, and whenever an entity's statements are large — its properties parameter selects individual P-IDs, granularity fields does not carry.
wikidata_get_labels
Resolve one or more QIDs or PIDs to their human-readable labels and descriptions. Lightweight — returns no claim data. Supports up to 50 IDs per call (batched automatically). Designed for the common agent pattern: receive QIDs from a SPARQL query, then humanize them.
wikidata_get_sitelinks
Fetch Wikipedia and Wikimedia project article URLs for a Wikidata item. A sitelink maps a site code (e.g., "enwiki") to a Wikipedia article title and URL. Major items can have 300+ sitelinks across languages. Use sites to filter to specific language editions, or wikis_only to return only Wikipedia links. Only Q-IDs (items) have sitelinks — properties (P-IDs) do not.
wikidata_get_statements
Fetch property claims for a Wikidata entity with qualifier and reference detail. Value QIDs are resolved to human-readable labels by default. Use the properties parameter to fetch only specific P-IDs — omitting it returns every statement, and a well-connected item (a country, a major city) carries hundreds of properties: more than fits inline. An oversized set comes back as kind: "outline" — every available P-ID with its byte size, largest first — instead of the statements; re-call with the same id plus properties:[...] naming the P-IDs you want. Designed for fact verification: "what does Wikidata say about this entity's {property}?". Preferred-rank statements are the most current values.
wikidata_resolve_external_id
Look up a Wikidata entity by an external identifier such as a DOI, PubMed ID, ORCID iD, or OpenAlex ID. Returns match=<entity> on success, match=null when not found, and match=null with multipleMatches populated when a Wikidata data integrity issue causes more than one entity to claim the same external ID. Common cross-server join use cases: CrossRef DOI → Wikidata paper QID (P356), PubMed PMID → Wikidata paper QID (P698), ORCID → author QID (P496), OpenAlex ID → entity QID (P10283). The property must be one whose Wikidata data type is external-id — item-valued or media properties (e.g. P31 instance-of, P18 image) are rejected rather than returning an empty match. Known value normalization is applied automatically: surrounding whitespace is trimmed, identifier-resolver URL prefixes are stripped (https://doi.org/, https://pubmed.ncbi.nlm.nih.gov/, https://orcid.org/), DOIs are uppercased, PMID prefixes stripped, ORCID hyphens normalized.
wikidata_search_entities
Search Wikidata for items or properties by text query. Returns QIDs or PIDs with labels, descriptions, and match metadata indicating whether the hit was on a label or alias. Use type="item" for real-world concepts (people, places, works) and type="property" to find predicate P-IDs. The API returns no total count — pagination is offset-based with no result ceiling indicator.
wikidata_sparql_query
Execute a SPARQL SELECT query against the Wikidata Query Service. Full graph power: multi-hop traversals, aggregations, subqueries, OPTIONAL, FILTER, UNION, BIND. Standard Wikidata prefixes (wd:, wdt:, p:, ps:, pq:, wikibase:, bd:) are auto-injected. The wikibase:label SERVICE is also auto-injected when language is set and the query includes ?<var>Label variables — so you can use ?itemLabel without writing the boilerplate. Hard server timeout is 60s; use LIMIT to keep queries fast. Bindings use the SPARQL 1.1 JSON format: each value is { type, value, "xml:lang"? }. Use wikidata_get_labels to humanize QID results from this tool.

Endpoints

URLTransportStateLatencyChecked
https://wikidata.caseyjhand.com/mcp streamable-http answering 428 ms 4 min ago

Wikidata MCP Server — questions

Answers built from our own checks of this server.

What can Wikidata MCP Server do?
It exposes 7 tools, read directly from the server on our last check. Among them: wikidata_get_entity, wikidata_get_labels, wikidata_get_sitelinks, wikidata_get_statements, wikidata_resolve_external_id, wikidata_search_entities and 1 more. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README. How MCP servers expose tools in the first place →
Is Wikidata MCP Server working right now?
We send a real MCP handshake every 15 minutes. Over the last 24 hours 91 of 91 checks got a reply (100.0%), average response time 391 ms. The bar chart above shows every period we have measured.
How do I connect Wikidata MCP Server?
Copy the ready config from this page — we generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each with the file path that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.
Does Wikidata MCP Server need an API key?
No. Wikidata MCP Server completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 7 of them are readable on this page. This is what we observed, not what the docs claim.
How fast is Wikidata MCP Server?
It answers our handshake in 391 ms on average, which is faster than 35% of all working MCP servers we measure. The comparison comes from our own checks across the whole registry, every 15 minutes.
How many people use Wikidata MCP Server?
The npm package @cyanheads/wikidata-mcp-server was installed 84 times in the last week. Week over week that is -43%. We show installs rather than GitHub stars on purpose: a star is a bookmark, an install is someone actually running it.
Is Wikidata MCP Server open source?
Yes — it is published under the Apache-2.0 licence, written in TypeScript, 2 stars on GitHub and 4 open issues. The source link is on this page, so you can read exactly what it does with your data before you connect it.