How to Use the Unbounce MCP in Vercel AI SDK

Q: How do I use Unbounce data with Vercel AI SDK?

You call mcpClient.tools() to expose the MCP Server's functions. Then, when generating text or streaming text, you reference the specific tool name (e.g., listpages). The results stream directly into your UI.

Q: If I need domain information for Unbounce, how does Vercel AI SDK help?

You use the listdomains tool. The data streams into your frontend, allowing you to display custom domains immediately without waiting for a traditional loading state or separate API call.

Display live Unbounce data streams directly into your Next.js or React frontend with Vercel AI SDK.

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Connect Unbounce MCP to Vercel AI SDK

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

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Show Live Account Info in Real Time

When you call `list_accounts` via the MCP Server, the results stream instantly to the user interface. You don't wait for a loading spinner; the data appears live. This real-time capability makes building complex dashboards simple. Your agent can fetch and display multiple datasets—like calling `get_me` or running `list_domains`—all while keeping the UI snappy.

Process Leads with Real-Time Feedback

The `get_lead` tool lets you pull specific lead details, and when paired with Vercel AI SDK, that data populates a form field immediately. It's perfect for user-facing tools. Imagine displaying the output of `list_leads` as it arrives. The end user sees the list populate in real time, giving them instant feedback on your agent's activity.

View Page Structure Live

You can fetch and display structure details using tools like `get_page` or listing form fields with `list_form_fields`. The data streams directly to the frontend. This avoids traditional API bottlenecks. You call the MCP Server, pass it the tool name, and stream the resulting JSON straight into your React components for immediate rendering.

Setup guide

Set up Unbounce 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 Unbounce 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 Unbounce transactions",
});

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

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Common questions about Unbounce MCP in Vercel AI SDK

You call `mcpClient.tools()` to expose the MCP Server's functions. Then, when generating text or streaming text, you reference the specific tool name (e.g., `list_pages`). The results stream directly into your UI.

Since the MCP Server exposes multiple tools, you'll be dealing with user details (`get_me`), account lists (`list_accounts`), and specific resource data like lead records (`list_leads`). All of this streams to your client.

Yes. Because the results stream in real-time, you can build multi-step processes where the user sees data arriving as it's fetched—for instance, listing sub-accounts via `list_sub_accounts` and then immediately using that list to fetch pages.

You use the `list_domains` tool. The data streams into your frontend, allowing you to display custom domains immediately without waiting for a traditional loading state or separate API call.

This MCP Server touches user-generated data types like lead records and account details. When building your product, make sure you handle all sensitive information according to standard best practices.

Use it with your favorite AI tools

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

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