Zengain MCP Server for Vercel AI SDKGive Vercel AI SDK instant access to 10 tools to Get Analytics Summary, Get Health Score, Get Product, and more
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Zengain through Vinkius and every tool is available as a typed function. ready for React Server Components, API routes, or any Node.js backend.
Ask AI about this App Connector for Vercel AI SDK
The Zengain app connector for Vercel AI SDK is a standout in the Data Analytics category — giving your AI agent 10 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
import { createMCPClient } from "@ai-sdk/mcp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";
async function main() {
const mcpClient = await createMCPClient({
transport: {
type: "http",
// Your Vinkius token. get it at cloud.vinkius.com
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
});
try {
const tools = await mcpClient.tools();
const { text } = await generateText({
model: openai("gpt-4o"),
tools,
prompt: "Using Zengain, list all available capabilities.",
});
console.log(text);
} finally {
await mcpClient.close();
}
}
main();
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Zengain MCP Server
Connect your Zengain (Nalpeiron Growth Platform) account to any AI agent and simplify your customer success and usage analytics workflows through natural conversation.
The Vercel AI SDK gives every Zengain tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 10 tools through Vinkius and stream results progressively to React, Svelte, or Vue components. works on Edge Functions, Cloudflare Workers, and any Node.js runtime.
What you can do
- Product Lifecycle — List all registered products and retrieve detailed configuration metadata
- User Engagement — Query product users, inspect their profiles, and calculate real-time health scores
- Usage Analytics — Get high-level analytics summaries and track custom events to monitor feature adoption
- KPM Tracking — Monitor Key Product Milestones to identify successful onboarding and churn risks
- System Monitoring — List configured webhooks to understand your integration data flow
The Zengain MCP Server exposes 10 tools through the Vinkius. Connect it to Vercel AI SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 10 Zengain tools available for Vercel AI SDK
When Vercel AI SDK connects to Zengain through Vinkius, your AI agent gets direct access to every tool listed below — spanning customer-success, product-analytics, lead-scoring, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Get analytics summary
Get customer health score
Get details for a specific product
Get details for a specific user
List tracking events
List Key Product Milestones
List Zengain products
List product users
List configured webhooks
Track a custom event
Connect Zengain to Vercel AI SDK via MCP
Follow these steps to wire Zengain into Vercel AI SDK. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
npm install @ai-sdk/mcp ai @ai-sdk/openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the script
agent.ts and run with npx tsx agent.tsExplore tools
Why Use Vercel AI SDK with the Zengain MCP Server
Vercel AI SDK provides unique advantages when paired with Zengain through the Model Context Protocol.
TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box
Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime. same Zengain integration everywhere
Built-in streaming UI primitives let you display Zengain tool results progressively in React, Svelte, or Vue components
Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency
Zengain + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Zengain MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Zengain in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Zengain tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Zengain capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Zengain through natural language queries
Example Prompts for Zengain in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Zengain immediately.
"List all products in my Zengain account."
"What is the health score for user 'customer_456'?"
"Show me a summary of usage analytics for this month."
Troubleshooting Zengain MCP Server with Vercel AI SDK
Common issues when connecting Zengain to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpZengain + Vercel AI SDK FAQ
Common questions about integrating Zengain MCP Server with Vercel AI SDK.
How does the Vercel AI SDK connect to MCP servers?
createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.Can I use MCP tools in Edge Functions?
Does it support streaming tool results?
useChat and streamText that handle tool calls and display results progressively in the UI.