Wikidata MCP, Ready to Go
Use the Wikidata MCP with your AI agents to query the world's largest knowledge graph for facts, SPARQL queries, and structured data.
No credit card required. Experience the power of this integration risk-free.
Query the world's largest open knowledge graph for facts and structured data.
Works with every AI agent you already use
…and any MCP-compatible client
How fast is the Wikidata Connector?
Average time for the server to become ready for requests over the last 14 days, measured until the initialize / tools/list handshake completes. Metrics are updated daily between 00:00 and 04:00 UTC. Create a free account, use this Connector on Vinkius Cloud, and connect it to your AI agent in seconds.
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What AI agents can do with Wikidata MCP: 8 Tools for Knowledge Graph Queries
Use these tools to query, search, and update the global Wikidata knowledge graph directly from your AI client.
Get item statements
Retrieve all statements for a specific Wikidata Item. Use this to get a full fact sheet on any entity.
Get item
Fetch a specific Wikidata Item via the Wikibase REST API. This is the quickest way to grab core data for a known ID.
Get similarity score
Compute similarity between a text string and a specific entity. This helps you rank how well a description matches a fact.
Search items vector
Perform a hybrid vector and keyword search for Items. It finds relevant entities based on context rather than just keywords.
Search properties vector
Perform a hybrid vector and keyword search for Properties. Use this to find specific attributes across the knowledge graph.
Set item description
Set an Item description using your credentials. This allows your agent to update the public description of a Wikidata entry.
Create statement
Create a new statement for an Item. Use this to add new facts to the knowledge graph when you have verified data.
Execute sparql
Execute a SPARQL query against the Wikidata Query Service. This lets you find complex patterns and data sets across the graph.
A Connector is a URL. Vinkius runs it: hosting, security, governance, observability.
You're looking at one of 5,800+ managed Connectors. The real value isn't the catalog. It's the control plane that secures, governs, audits, and manages every interaction between your agents and the tools they use.
No Shadow AI
Every agent action is visible, approved, and auditable. Nothing runs outside your governance.
Absolute agent control
Fine-grained permissions for every agent, MCP, and tool. Instantly revoke access and audit every execution.
Cost control per token
Spend broken down to the token, tool, and agent. Budgets and hard limits. No surprise invoices.
Managed & monitored infra
We operate the runtime, authentication, scaling, retries, and monitoring. Your team manages AI, not infrastructure.
Data protection, DLP by design
Sensitive data is filtered before reaching the model. Access is governed so agents receive only the information they're allowed to use.
Token optimization, real savings
Lower AI costs by delivering the right context instead of unnecessary tools. Better accuracy, faster responses, and fewer wasted tokens.
Fact-Checking with the Wikidata MCP for AI Agents
This is for anyone who needs to move past hallucinations and get hard facts. It's for the researcher who needs to verify dates, the data scientist who needs clean datasets, and the developer who needs to map out entity schemas.
Academic Researcher
Verifying historical dates and cultural relationships during a literature review.
Data Scientist
Pulling structured datasets for training models without leaving the chat interface.
Backend Developer
Finding property schemas and entity IDs to build out a data-rich application.
Frequently Asked Questions
What is the Wikidata MCP for AI Agents? +
It's a tool that lets your AI client connect to the world's largest open knowledge graph. You can use it to pull real-world facts, run complex queries, and find data based on meaning.
Can I use the Wikidata MCP to update facts? +
Yes, you can update descriptions or create new statements. You just need to provide an OAuth 2.0 token in your configuration to enable these write actions.
Does the Wikidata MCP support complex queries? +
Yes, it supports SPARQL, which is the standard query language for the knowledge graph. This allows you to find complex relationships and specific datasets.
How does the Wikidata MCP help with research? +
It lets you instantly verify dates, populations, and relationships. Instead of searching manually, your agent pulls verified data directly into your conversation.
Can my agent find things by meaning with the Wikidata MCP? +
Yes, it includes vector search tools. This means your agent can find relevant items based on the context of your question rather than just looking for exact keywords.
What do I need to provide to get the Wikidata MCP working? +
You just need to subscribe on Vinkius and provide a User Agent. If you want to edit data, you'll also need to add an OAuth 2.0 token.
How can I find a Wikidata Item if I don't know its Q-ID? +
You can use the search_items_vector tool. It performs a hybrid search using high-dimensional embeddings and keywords to find the most relevant entities based on your natural language description.
Is it possible to run complex queries like 'List all female scientists born in the 19th century'? +
Yes, the execute_sparql tool allows you to run any valid SPARQL query against the Wikidata Query Service. This is the most powerful way to filter and aggregate data across the entire knowledge graph.
Can I use this server to update information on Wikidata? +
Yes, if you provide an OAuth 2.0 Access Token, you can use create_statement to add new data or set_item_description to update descriptions in various languages.
Your AI, connected to everything.
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