How to Use the Curve Fitting Engine MCP in Vercel AI SDK

Get math-perfect regression coefficients inside your Vercel AI SDK app. Stream live curve fitting data directly to your users.

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Connect Curve Fitting Engine MCP to Vercel AI SDK

Create your Vinkius account to connect Curve Fitting Engine to Vercel AI SDK 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 Vercel AI SDK

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Real-time regression in your UI

Feed your scatter plot coordinates into the `calculate_regression` tool to get immediate mathematical outputs. Your front-end components render the results as the data arrives. Stop waiting for background jobs to finish. The Vercel AI SDK streams these coefficients to your browser so the user watches the trend line snap into place.

Deterministic math for front-end apps

This MCP server handles the heavy lifting of Linear and Polynomial regression locally. You avoid client-side math errors by offloading the logic to this specialized engine. The `calculate_regression` function returns clean, formatted equations and R-squared scores ready for your state management. It keeps your bundle size small while maintaining high-precision calculations.

Edge-ready mathematical analysis

Deploy your app to the edge and compute complex trends without needing a full-blown backend database or heavy math libraries. Your AI agent triggers the `calculate_regression` tool to process user inputs on the fly. It provides consistent, reliable math that makes your Vercel AI SDK projects feel fast and responsive.

Setup guide

Set up Curve Fitting Engine MCP in Vercel AI SDK

Prerequisites

Node.js 18+ and a TypeScript project
ai + @modelcontextprotocol/sdk packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies

Run npm install ai @modelcontextprotocol/sdk plus your preferred model provider (e.g. @ai-sdk/openai).
2

Create the Streamable HTTP transport

Use StreamableHTTPClientTransport with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and use tools

Call mcpClient.tools() to auto-discover all Curve Fitting Engine tools. Pass them directly to generateText() or streamText() — no manual schema definitions needed.
4

Works with any model provider

Swap openai("gpt-4o") for any AI SDK provider — Anthropic, Google, Mistral. The MCP tools work identically across all supported models.

index.ts

import { experimental_createMCPClient as createMCPClient } from "ai";
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";

const transport = new StreamableHTTPClientTransport(
  new URL("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
);

const mcpClient = await createMCPClient({ transport });
const tools = await mcpClient.tools();

const { text } = await generateText({
  model: openai("gpt-4o"),
  tools,
  prompt: "List recent Curve Fitting Engine transactions",
});

console.log(text);
await mcpClient.close();

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Common questions about Curve Fitting Engine MCP in Vercel AI SDK

Install the MCP client package and initialize the connection with your server URL. You then pass the `calculate_regression` tool into your streamText function to start processing.

It manages scatter plot data efficiently by performing calculations on the server side. You get the results back as a structured object, keeping your UI thread free for rendering.

The server processes regression tasks in milliseconds. Since it connects via HTTP, your app remains snappy while the agent performs the math.

You get exact deterministic coefficients every time. It uses standard regression algorithms that provide consistent outputs for your front-end visualizations.

Your scatter plot data travels over an encrypted connection and remains within your session context. We never store your numbers or coefficients after the request finishes.

Use it with your favorite AI tools

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