How to Use the Carbonara MCP in Vercel AI SDK

Turn your code blocks into PNG images instantly using the Carbonara MCP server within the Vercel AI SDK.

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Connect Carbonara MCP to Vercel AI SDK

Create your Vinkius account to connect Carbonara 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 Carbonara with Vercel AI SDK

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Visualizing code in Vercel AI SDK

Use the `cook_code_image` tool to convert raw text into a styled PNG. Your React components receive the base64 string directly, allowing you to render code snapshots without waiting for a backend round trip. This MCP server keeps your UI responsive. Since the result streams into your frontend, users see the image manifest as soon as the agent finishes the request.

Real-time image rendering

Inject the output of `cook_code_image` into your Next.js application flow. Your interface displays the code graphic while the agent continues to process subsequent tasks. It removes the need for external image hosting services. You get the bits directly from the MCP server and pipe them into an image tag.

Building UI-first code tools

Develop documentation generators or chat interfaces that output visual code previews. By calling the `cook_code_image` tool, you ensure every snippet shared in your app looks consistent and readable. Your users get a polished view of their work. The tool handles the syntax highlighting and window controls so your frontend only worries about layout.

Setup guide

Set up Carbonara 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 Carbonara 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 Carbonara transactions",
});

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

Get your connection token →

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Common questions about Carbonara MCP in Vercel AI SDK

Install the MCP client package and initialize the connection with your server URL. You can then pass the tools directly into your streamText function.

Yes. The server returns base64 data that flows right into your UI components during the generation process.

Just set up the transport layer using the standard MCP client. Once connected, your agents gain immediate access to the image rendering tool.

The server generates a PNG snapshot. It is a static image file that you can save or display anywhere in your app.

This server processes raw text snippets to create images. It does not store your code or metadata on our servers, ensuring your source remains private.

Use it with your favorite AI tools

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

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