How to Use the Curve Fitting Engine MCP in VS Code Copilot

Q: Is my scatter plot data safe when using this MCP Server with VS Code Copilot?

Completely. The server configuration in .vscode/mcp.json can point to a local binary. In that setup, your scatter plot data is handled by the Copilot agent and passed to the local process on your workstation, never sent to an external service.

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Connect Curve Fitting Engine MCP to VS Code Copilot

Create your Vinkius account to connect Curve Fitting Engine to VS Code Copilot 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 Curve Fitting Engine with VS Code Copilot

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Standardize Analysis Across Your Team

Commit a `.vscode/mcp.json` file to your repository. Now every developer on the team gets access to the Curve Fitting Engine. No individual setup, no 'it works on my machine' problems. Everyone uses the same `calculate_regression` tool. This is how you enforce consistency. When anyone on the team asks Copilot to model a dataset, it uses this exact MCP server. The math is always deterministic and correct because it's part of your team's shared tooling.

An MCP Server Built for Team Repos

Copilot Chat becomes a powerful, shared analysis tool. Any engineer can highlight data in a file and ask the agent to find a trend line. The agent uses the `calculate_regression` tool and can even draft a comment explaining the model. This is especially useful for code reviews. You can ask Copilot to analyze performance benchmark data right in the PR. The results are reproducible by any teammate who pulls the branch, since the MCP configuration is part of the project.

Integrate Regression into Your Workflow

This is more than just a chat command. Because it's a standard tool, you can build it into automated scripts. Think about a pre-commit hook where Copilot checks for performance regressions by running a curve fit on new benchmark data. You can also use it to document changes. Ask Copilot to run `calculate_regression` on a set of metrics and append the resulting equation to a README file. It's a simple way to track trends with every commit.

Setup guide

Set up Curve Fitting Engine MCP in VS Code Copilot

Prerequisites

VS Code 1.99 or later with GitHub Copilot extension
Active Vinkius subscription with a valid endpoint token

1

Open MCP configuration

Open the Command Palette (Cmd+Shift+P / Ctrl+Shift+P) and run "MCP: Add Server". Select HTTP (Streamable) as the server type. VS Code will create .vscode/mcp.json in your workspace.
2

Add the Curve Fitting Engine MCP

Paste the JSON snippet shown on the right into your .vscode/mcp.json. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Switch to Agent mode

Open Copilot Chat (Cmd+Shift+I / Ctrl+Shift+I) and switch to Agent mode using the dropdown. MCP tools are only available in Agent mode — they do not appear in Edit or Ask modes.
4

Verify the connection

In the Copilot Chat input, type # to list available tools. You should see the Curve Fitting Engine tools listed. Try asking: "List my recent Curve Fitting Engine transactions" and Copilot will invoke them automatically.

.vscode/mcp.json

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

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Common questions about Curve Fitting Engine MCP in VS Code Copilot

A project lead just needs to add the server's configuration to a `.vscode/mcp.json` file and commit it to your Git repo. Once team members pull that change, Copilot automatically has access to the tool.

Yes, it's designed for Agent mode. Copilot can autonomously decide to use the `calculate_regression` tool when you ask it an analysis question about data in your editor. It handles running the tool and interpreting the results for you.

The server itself is a stateless tool for calculations. When used with VS Code Copilot in an enterprise setting, it runs within your existing infrastructure, which can be part of a SOC 2 compliant environment. Vinkius-hosted servers also operate in a secure, compliant cloud.

It's about team-wide access and standardization. By putting the MCP Server config in your repo, everyone gets the same vetted tool. This prevents team members from writing their own, slightly different, and possibly wrong analysis scripts.

Completely. The server configuration in `.vscode/mcp.json` can point to a local binary. In that setup, your scatter plot data is handled by the Copilot agent and passed to the local process on your workstation, never sent to an external service.

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