How to Use the data.world MCP in Cursor

Q: How do I import data.world schemas into Cursor?

Ask the Cursor agent to inspect a dataset. It will invoke getdatasetdetails to fetch field definitions and write code that matches your live database schema.

Q: Can Cursor access my saved data.world queries?

Yes. This MCP server allows your agent to use listdatasetqueries to read your saved SQL and SPARQL. You can paste or refactor them directly in your active file.

Q: Can I manage my data.world collections from the editor?

Yes. The listmycollections tool lists your owned and managed collections. This gives your agent immediate visibility into how your assets are grouped.

Write code against real data.world schemas and saved queries inside Cursor using live workspace metadata.

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Connect data.world MCP to Cursor

Create your Vinkius account to connect data.world to Cursor 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 data.world with Cursor

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Build code with live data.world schemas

The `get_dataset_details` tool pulls live schemas, field definitions, and file lists directly into your Cursor editor. Your coding agent reads these structures to write accurate data models without relying on outdated documentation. This eliminates the need to manually copy-paste table structures. You get clean, working code that matches your actual database catalog on the first run.

Inject saved SQL directly into Cursor

The `list_dataset_queries` tool retrieves saved SQL and SPARQL queries directly from your data.world account. Your agent uses these snippets to generate API calls or database connectors in your local codebase. This MCP Server setup ensures your code uses production-tested queries instead of guessed syntax. It makes writing database integration tests significantly faster.

Access project insights while you code

The `list_project_insights` tool fetches documented findings and data visualizations attached to your workspace. Your agent reads these insights to understand the business logic behind the data you are processing. You can also use `get_project_details` to map out project members and linked resources. It keeps your development aligned with the broader data team's goals.

Setup guide

Set up data.world MCP in Cursor

Prerequisites

Cursor installed (macOS, Windows, or Linux)
Active Vinkius subscription with a valid endpoint token

1

Open MCP Settings

Go to Cursor Settings → MCP or open the Command Palette (Cmd+Shift+P / Ctrl+Shift+P) and search for "MCP: Add Server".
2

Add the data.world MCP

Cursor will create or open .cursor/mcp.json in your project root. Paste the JSON snippet on the right. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Enable Agent mode

Open Composer (Cmd+I / Ctrl+I) and switch to Agent mode using the dropdown at the top. MCP tools are only available in Agent mode.
4

Verify the connection

Ask Cursor something like "List my recent data.world transactions." If the MCP tools are loaded correctly, Cursor will call the data.world tools automatically. You can also check Settings → MCP for a green status indicator.

.cursor/mcp.json

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

Get your connection token →

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Common questions about data.world MCP in Cursor

Ask the Cursor agent to inspect a dataset. It will invoke `get_dataset_details` to fetch field definitions and write code that matches your live database schema.

Yes. This MCP server allows your agent to use `list_dataset_queries` to read your saved SQL and SPARQL. You can paste or refactor them directly in your active file.

Use the chat panel to run a search. The data.world MCP server executes the `search_catalog` tool to find matching datasets and projects across your organization.

Yes. The `list_my_collections` tool lists your owned and managed collections. This gives your agent immediate visibility into how your assets are grouped.

No. All requests run through an ephemeral, zero-trust sandbox. Your query definitions and schema details are processed in memory and never stored, ensuring your intellectual property remains private.

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