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How to Use the ANOVA Calculator Engine MCP in Windsurf

Run exact One-Way ANOVA tests directly inside Windsurf without letting Cascade guess the math.

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Windsurf

Connect ANOVA Calculator Engine MCP to Windsurf

Create your Vinkius account to connect ANOVA Calculator Engine to Windsurf 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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Cascade chains data prep with the ANOVA MCP Server.

Stop letting your agent guess statistical significance when running the `calculate_anova` tool. When you feed raw CSV files or database queries to Windsurf, Cascade can automatically clean the data and pass it directly to the engine. It gets back real CPU-calculated F-scores and p-values instead of hallucinated math. You do not have to copy-paste numbers into Python scripts. Cascade plans the whole pipeline, runs the math through this MCP server, and presents the final statistical table right in your chat panel.

Automate multi-group comparisons in your workspace.

This server lets Windsurf execute `calculate_anova` directly on your active workspace files. Working with multiple experimental groups usually means writing boilerplate statistical code. Cascade reads your directory, identifies the sample groups, and runs the calculations. It handles the grouping and outputs exact p-values so you can immediately see if your test results are actually significant.

Eliminate LLM math errors during interactive debugging.

LLMs are bad at variance calculations, so this server lets you run `calculate_anova` on your local CPU. When you ask Windsurf to analyze experimental runs, Cascade bypasses its own token-generation math to secure true values. This guarantees that your statistical tests are mathematically perfect. You get the speed of an autonomous agent combined with the raw accuracy of a local statistical calculator.

Setup guide

Set up ANOVA Calculator Engine MCP in Windsurf

Prerequisites

  • Windsurf IDE installed (macOS, Windows, or Linux)
  • Active Vinkius subscription with a valid endpoint token
  1. 1

    Open MCP configuration

    Click the Cascade assistant icon in the sidebar, then click the hammer icon (🔨) at the top of the panel. Select "Configure" to open ~/.codeium/windsurf/mcp_config.json.

  2. 2

    Add the ANOVA Calculator Engine MCP

    Paste the JSON snippet shown on the right into the mcpServers object. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.

  3. 3

    Refresh MCPs

    Go back to the hammer icon (🔨) in Cascade and click "Refresh". Windsurf will detect the new server. No full restart is needed — the connection is hot-reloaded.

  4. 4

    Verify in Cascade

    Start a new Cascade conversation and ask something like "Show my ANOVA Calculator Engine payment history." If connected, Cascade will call the ANOVA Calculator Engine tools directly. You will see a green dot next to the server name in the MCP panel.

mcp_config.json
{
  "mcpServers": {
    "anova-calculator-engine-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

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Common questions about ANOVA Calculator Engine MCP in Windsurf

Cascade calls the `calculate_anova` tool when you ask it to analyze group means. It passes your raw dataset directly to the local server, bypassing token-based math to return exact F-scores.
Yes. The server processes your numerical groups locally on your machine, meaning Windsurf can analyze thousands of data points without hitting LLM context limits or timing out.
You can add it directly to your `~/.codeium/windsurf/mcp_config.json` file under the `mcpServers` key. Once saved, Cascade immediately detects the statistical tools.
No. The server runs standalone and handles the math internally. Windsurf simply sends the raw group numbers to the tool and displays the exact output.
Your numeric group data never leaves your machine. This MCP server runs entirely within a local V8 sandbox, meaning Windsurf processes your experimental samples locally without uploading them to external statistical APIs.

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