How to Use the Chi-Square Test Engine MCP in Cursor

Q: How does the Chi-Square Test Engine work with Cursor's Agent mode?

Once you configure the MCP Server in your mcp.json file, Cursor's agent can invoke the calculatechisquare tool. It will send your contingency table data to the tool and return the exact statistical results.

Q: What's the setup for the Chi-Square Test Engine in Cursor?

Create a .cursor/mcp.json file in your project's root directory. Then, add the server's configuration details. Cursor will automatically pick it up and make the tool available to the agent.

Inject real chi-squared stats and p-values directly into your Python scripts using Cursor's agent mode.

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Connect Chi-Square Test Engine MCP to Cursor

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Setup Chi-Square Test Engine with Cursor

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Generate Code with Real Data

The `calculate_chi_square` tool feeds actual statistical results into Cursor's code generation. When you ask the agent to run a test, it calls the tool and then writes Python or R code using the real p-value and chi-squared statistic it just calculated. This means no more placeholder values or mock data in the code your agent writes. It generates working, data-driven scripts from the first draft.

Run Stats Without Leaving Your Editor

You don't have to switch to a Jupyter notebook or RStudio just to run one quick test. With this MCP tool installed, you can stay in your flow. Just highlight a data structure in your code, ask for a chi-square test, and get the result back in seconds. Cursor's agent mode handles the call to the `calculate_chi_square` tool for you. It's a simple way to integrate statistical validation directly into your coding process.

A Reliable MCP Server for Your Agent

Avoid shipping code that relies on your agent's fuzzy math. This tool provides a proper stats function, exposed to your agent through a managed MCP Server, so you can trust the numbers it injects into your code. The calculation is deterministic and repeatable. It's the right way to use an AI agent for tasks that demand precision.

Setup guide

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

.cursor/mcp.json

{
  "mcpServers": {
    "chi-square-test-engine-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

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Common questions about Chi-Square Test Engine MCP in Cursor

Once you configure the MCP Server in your `mcp.json` file, Cursor's agent can invoke the `calculate_chi_square` tool. It will send your contingency table data to the tool and return the exact statistical results.

Yes. You can ask the agent to generate a unit test that uses a known contingency table and asserts that the calculated p-value from the tool matches the expected outcome. It's great for building statistical validation into your test suite.

Create a `.cursor/mcp.json` file in your project's root directory. Then, add the server's configuration details. Cursor will automatically pick it up and make the tool available to the agent.

This tool is built for one job: performing a deterministic Chi-Square test. It doesn't approximate. If your agent needs a mathematically correct chi-squared statistic and p-value, this is the right tool to use.

Your contingency table data is sent from your Cursor editor to the Vinkius-managed server for processing. The connection is encrypted, and the MCP Server itself runs in a zero-trust, ephemeral sandbox. Your data is only used for the calculation and is immediately discarded.

Use it with your favorite AI tools

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