How to Use the Curve Fitting Engine MCP in Cursor

Generate Python or JS code with real regression models baked in, all inside the Cursor editor.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Curve Fitting Engine MCP to Cursor

Create your Vinkius account to connect Curve Fitting 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.

GDPR Free for Subscribers

Setup Curve Fitting Engine with Cursor

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Turn Raw Data Into Working Code

Highlight a block of data points in your editor—maybe from a test file or a log. Tell the Cursor agent to 'fit a curve to this data.' It calls `calculate_regression` and gets the precise coefficients for a linear or polynomial model. Then, the agent writes the code for you. It can generate a Python function using those coefficients to make predictions, or a JavaScript snippet to plot the curve. You go from raw data to working code in one step.

Build Models Without Mocking Data

Stop writing stub functions for your data science code. With this MCP Server, Cursor's agent can use `calculate_regression` to build models from actual data. The code it generates is based on the real mathematical fit, not a placeholder. This is a huge time-saver. You're not just getting boilerplate. You're getting functional code that already incorporates the analysis, which is perfect for prototyping data visualizations or building out predictive features.

Refine Models Directly in Your Editor

The first fit isn't always the best. After Cursor generates the initial code, you can ask for changes. 'Try a 3rd-degree polynomial instead' or 'What's the R-squared on that?' The agent re-runs the tool and updates the code in place. This tight feedback loop happens entirely within your editor. You don't have to switch to a notebook or another app to do the math. You stay in your flow, refining the model and the code at the same time.

Setup guide

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

.cursor/mcp.json

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by ml-regression. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Curve Fitting Engine now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Curve Fitting Engine MCP in Cursor

Once you've configured the MCP server in your project's mcp.json, just use Agent mode. You can then instruct the agent to analyze data in your open files. It will call `calculate_regression` automatically and use the results to write or modify your code.

Yes. After the engine returns the regression coefficients, you can ask the Cursor agent to 'use these coefficients to generate a Plotly graph in Python.' The agent combines the tool's output with its own coding knowledge to create the exact snippet you need.

No. You can run the server locally and point to it from your `mcp.json` file. This is the best way to work with sensitive data or when you're offline.

Speed. You don't have to context-switch. The entire process—from analyzing data to generating code that uses the analysis—happens in one place. Cursor's agent bridges the gap between the mathematical model and the implementation.

Yes. If you run the server locally, your scatter plot data is passed from the Cursor editor to the local server process via your project's configuration. It never leaves your machine.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript