How to Use the Zengain MCP in Vercel AI SDK

Q: How does Zengain work with Vercel AI SDK?

The MCP Server exposes all of Zengain's data tools (like listusers or getanalyticssummary) as streamable endpoints. Your agent calls the tool, and the results flow straight into your Next.js frontend.

Q: What kind of data does the Zengain MCP Server touch?

This server handles customer profiles, product catalogs (listproducts), user details (getuserdetails), and event tracking data. Everything is exposed via tool calls.

Q: If I want user details, which tool should I use with Zengain and Vercel AI SDK?

Use getuserdetails. It takes a specific identifier and immediately returns the profile data. This is the most direct way to show a user's current standing in your application.

Show off real-time analytics data in your Next.js frontend with Vercel AI SDK.

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Connect Zengain MCP to Vercel AI SDK

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

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Stream User Data into the UI

Need to show a user's current health status? Call `get_health_score` and stream the result directly into your React component. Users see the score pop up instantly, without having to wait for a loading state. This real-time feedback is critical when building interactive tools. Your agent can run complex queries, like pulling product details via `get_product`, and display the output immediately as it arrives.

Monitor Website Activity Live

Keep track of user behavior on your site using tracking events. You can call `list_events` to see a feed of all recent actions taken across your platform. It’s perfect for building real-time dashboards. Want to capture something new? Use `track_event` to log custom data points. The Vercel AI SDK handles this stream smoothly, making the user experience feel native and immediate.

Get Core Business Insights

You've got a bunch of raw numbers; you need summaries. Calling `get_analytics_summary` gives you immediate context on performance trends. This lets your client build dashboards that react to data in real time. Beyond general analytics, check out the specific metrics available with `list_kpms`. Streaming these Key Product Milestones right into the UI makes the insights feel tangible and actionable for the end-user.

Setup guide

Set up Zengain 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 Zengain 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 Zengain transactions",
});

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Zengain. 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 Zengain MCP in Vercel AI SDK

The MCP Server exposes all of Zengain's data tools (like `list_users` or `get_analytics_summary`) as streamable endpoints. Your agent calls the tool, and the results flow straight into your Next.js frontend.

This server handles customer profiles, product catalogs (`list_products`), user details (`get_user_details`), and event tracking data. Everything is exposed via tool calls.

Yes. You can track high-intent visitors by listing events or checking the general analytics summary. The resulting data streams into your UI, letting you build lead monitoring dashboards.

No. Because it's designed for streaming directly to a frontend framework like Next.js, the data handling is abstracted away from traditional backend API calls, making deployment simpler.

Use `get_user_details`. It takes a specific identifier and immediately returns the profile data. This is the most direct way to show a user's current standing in your application.

Use it with your favorite AI tools

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