How to Use the K-Fold Split Engine MCP in Cursor

Q: How do I add the K-Fold Split Engine to my Cursor project configuration?

Create a .cursor/mcp.json file in your root folder and add the K-Fold Split Engine configuration. This registers the calculatekfold tool so your Cursor Agent can call it during active coding sessions.

Generate leak-free validation indices directly in your Cursor editor using the K-Fold Split Engine.

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Connect K-Fold Split Engine MCP to Cursor

Create your Vinkius account to connect K-Fold Split Engine 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 K-Fold Split Engine with Cursor

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Generate validation indices directly inside Cursor files

The `calculate_kfold` tool calculates index arrays directly inside your Cursor workspace to partition your machine learning datasets using the K-Fold Split Engine. It prevents your Cursor agent from writing buggy, manual array-slicing code that causes validation leakage. The K-Fold Split Engine outputs exact integer boundaries that your Cursor editor injects directly into your active Python script. You get mathematically sound splits without manual math inside Cursor.

Let your Cursor Agent write code with real split data

The `calculate_kfold` tool provides raw index data that your Cursor Agent reads to build operational training pipelines. Instead of generating placeholder code with dummy arrays, Cursor writes code tailored to your exact dataset dimensions using the K-Fold Split Engine. This integration allows the Cursor editor to verify that your training loops match the exact index output of the K-Fold Split Engine. The Cursor agent can immediately run the script to test the split configuration.

Configure this MCP Server for specific Cursor projects

The `calculate_kfold` tool relies on a project-scoped `.cursor/mcp.json` file to manage the K-Fold Split Engine parameters. This local Cursor configuration ensures that every developer working on the project uses the exact same split parameters. By declaring the MCP Server in your Cursor repository, the editor automatically maps the index generation tools to your active workspace. This keeps your K-Fold Split Engine cross-validation pipeline consistent across different Cursor developer machines.

Setup guide

Set up K-Fold Split Engine 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 K-Fold Split Engine 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 K-Fold Split Engine transactions." If the MCP tools are loaded correctly, Cursor will call the K-Fold Split Engine tools automatically. You can also check Settings → MCP for a green status indicator.

.cursor/mcp.json

{
  "mcpServers": {
    "k-fold-split-engine-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

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Common questions about K-Fold Split Engine MCP in Cursor

Create a `.cursor/mcp.json` file in your root folder and add the K-Fold Split Engine configuration. This registers the `calculate_kfold` tool so your Cursor Agent can call it during active coding sessions.

Yes, when you enable Agent mode in Cursor, the editor can call the K-Fold Split Engine to generate validation indices. The Cursor agent then writes the training loop around the returned index arrays.

No, the K-Fold Split Engine only handles index math within Cursor. It returns integer lists representing rows, meaning your actual tabular feature data is never sent to the Cursor LLM.

Writing split code manually in Cursor often leads to off-by-one errors and subtle index leakage. The K-Fold Split Engine provides tested, mathematical indices that guarantee zero overlap between your training and test folds in Cursor.

The K-Fold Split Engine only processes dataset row counts and fold parameters to output index arrays. Your raw CSV or database rows remain in your local Cursor workspace, untouched by the MCP Server.

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