How to Use the GoZen Testimonials MCP in Vercel AI SDK

Q: How do I install GoZen Testimonials with Vercel AI SDK?

Run npm install ai @ai-sdk/mcp to get started. Initialize the client with createMCPClient using the Vinkius HTTP endpoint, then pass the tools array directly into streamText.

Q: Can Vercel AI SDK stream video testimonials from GoZen Testimonials?

Yes, the SDK streams the metadata returned by listtestimonials directly to your frontend components. This allows your UI to render video players and customer quotes without waiting for full page reloads.

Q: How do I clean up the connection after fetching widgets?

Always call mcpClient.close() when your application finishes executing the tool calls. This prevents connection leaks and keeps your Next.js serverless functions running efficiently.

Q: Does this setup support private forms?

The getform tool retrieves specific form configurations, which you can filter or hide behind your own application's authentication layer. The GoZen Testimonials MCP Server acts as the secure intermediary between your user and the GoZen API.

Build live-streaming social proof dashboards in Next.js using Vercel AI SDK and the GoZen Testimonials MCP Server.

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Connect GoZen Testimonials MCP to Vercel AI SDK

Create your Vinkius account to connect GoZen Testimonials 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 GoZen Testimonials with Vercel AI SDK

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Live Testimonial Moderation inside Vercel AI SDK

The `approve_testimonial` tool updates the status of customer submissions instantly. Your AI client calls this tool to publish approved video feedback straight to your UI without requiring manual dashboard clicks. Because Vercel AI SDK streams tool calls directly to your React components, users see the updated status change in real time. You don't have to write custom polling logic or handle loading spinners while waiting for the database to update.

Instant Form Provisioning for Next.js Apps

The `create_form` tool generates branded video recording pages for your customers. Your agent triggers this tool whenever a customer agrees to provide feedback, immediately returning the form URL. By using this MCP Server with `streamText`, the generated form URL appears in your chat interface as soon as the API responds. This cuts down on user friction and gets the collection page in front of the customer within seconds.

Feed Live Widgets into Edge Functions

The `create_widget` tool configures embeddable display layouts to showcase your video testimonials. Your AI client reads current widgets via `list_widgets` and spins up new ones based on the customer's current page context. Running this workflow inside Edge Functions ensures minimal latency. The SDK streams the new widget configuration directly into your layout, letting you display social proof to visitors instantly.

Setup guide

Set up GoZen Testimonials 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 GoZen Testimonials 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 GoZen Testimonials transactions",
});

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

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 GoZen Testimonials. 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.

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Common questions about GoZen Testimonials MCP in Vercel AI SDK

Run `npm install ai @ai-sdk/mcp` to get started. Initialize the client with `createMCPClient` using the Vinkius HTTP endpoint, then pass the tools array directly into `streamText`.

Yes, the SDK streams the metadata returned by `list_testimonials` directly to your frontend components. This allows your UI to render video players and customer quotes without waiting for full page reloads.

Always call `mcpClient.close()` when your application finishes executing the tool calls. This prevents connection leaks and keeps your Next.js serverless functions running efficiently.

The `get_form` tool retrieves specific form configurations, which you can filter or hide behind your own application's authentication layer. The GoZen Testimonials MCP Server acts as the secure intermediary between your user and the GoZen API.

Your customer video files and form configurations are protected by Vinkius's isolated V8 sandboxes. The connection token is injected securely at runtime, ensuring your API keys never leak to the client browser.

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