How to Use the Wikidata MCP in Cline

Q: How do I start a Wikidata query using Cline?

Just tell Cline the goal. It will use executesparql to run the query, returning structured results that you can immediately process or test against within your coding environment.

Q: Can Cline find items by name or description?

Yeah. You've got two main vector search tools: searchitemsvector and searchpropertiesvector. They handle hybrid searches, so you can combine keywords with semantic understanding.

Q: What is the best way to check if an item exists in Wikidata using Cline?

Start with getitem(g., Q42) for a quick look at core data. If that's not enough, run getitemstatements to pull every single recorded fact and relationship.

Q: If I need to update Wikidata, what do I use in Cline?

You'll use the createstatement tool. It writes a new structured statement for an Item. Be sure your environment has the OAuth 2.0 Access Token ready.

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Connect Wikidata MCP to Cline

Create your Vinkius account to connect Wikidata to Cline and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Wikidata with Cline

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MCP Server: Advanced Querying

Cline lets you run complex SPARQL queries against Wikidata, giving you structured data right where you write code. You can execute the query using `execute_sparql` and then immediately use that output to populate a component or pass it to another function. The agent even suggests using a 'None' hint for the optimizer if your queries start timing out. It makes dealing with large datasets painless.

Entity Resolution and Similarity

Don't just rely on ID lookups. Cline helps you find items by similarity. Run `get_similarity_score` to compare text against an entity, or use the vector search tools (`search_items_vector`, `search_properties_vector`) for hybrid keyword/vector searches. This means your code can handle messy, real-world input and still pull accurate Wikidata data.

Full Item Lifecycle Management

You can treat the item lifecycle as a coding task. First, use `get_item` to grab basic details. Then, if you need depth, fetch all statements with `get_item_statements`. If your goal is data modification, you'll use `create_statement`, remembering that OAuth 2.0 access is necessary. This sequence lets Cline perform end-to-end data manipulation tasks.

Setup guide

Set up Wikidata MCP in Cline

Prerequisites

VS Code with Cline extension installed
Active Vinkius subscription with a valid endpoint token

1

Open Cline MCP settings

Click the Cline icon in the VS Code sidebar to open the Cline panel. Then click the MCP Servers icon (server stack) at the top-right corner of the panel.
2

Add a remote server

Click "Remote Servers" at the top, then click "Add Remote MCP". In the Name field, type wikidata-mcp. In the URL field, paste your Vinkius endpoint: https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp. Get your token from cloud.vinkius.com.
3

Enable the server

After saving, the server appears in the Cline MCP panel. Toggle the switch to enable it. The status indicator turns green when the connection is live.
4

Start using tools

Return to the Cline chat and ask: "Check my latest Wikidata refund status." Cline will discover the available tools and request your approval before invoking each one — giving you full control over every action.

Cline MCP Settings

{
  "mcpServers": {
    "wikidata-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Wikidata. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Wikidata MCP in Cline

Just tell Cline the goal. It will use `execute_sparql` to run the query, returning structured results that you can immediately process or test against within your coding environment.

Yeah. You've got two main vector search tools: `search_items_vector` and `search_properties_vector`. They handle hybrid searches, so you can combine keywords with semantic understanding.

Start with `get_item(g., Q42)` for a quick look at core data. If that's not enough, run `get_item_statements` to pull every single recorded fact and relationship.

You'll use the `create_statement` tool. It writes a new structured statement for an Item. Be sure your environment has the OAuth 2.0 Access Token ready.

This MCP Server deals with public, structured facts stored as 'statements' (triples). You are working directly with the world's open knowledge graph.

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