How to Use the Zengain MCP in Mastra AI

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

It touches all core business data: product inventory (listproducts), user accounts (listusers), conversion metrics (gethealthscore), and webhooks configuration.

Build complex, fault-tolerant workflows with Zengain using Mastra AI.

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Connect Zengain MCP to Mastra AI

Create your Vinkius account to connect Zengain to Mastra AI 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 Mastra AI

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Run Multi-Step Data Investigations

You don't just need one piece of data; you need a sequence. Use Mastra AI to chain together actions, like first calling `list_products` and then running `get_product` for each item found. The workflow engine manages the entire process. If the initial product search fails, the system doesn't crash. It automatically retries or moves to a fallback step, ensuring your data pipeline remains stable.

Manage User and Account Lifecycle

Handling user accounts requires precision. Set up a workflow that first calls `list_users` to check existence, then runs `get_user_details`, and finally triggers an action like tracking an event via `track_event`. Mastra AI handles the conditional logic here. This reliability is key. If the user data endpoint times out, your agent knows exactly how to handle that failure without needing manual intervention.

Analyze Business Health Over Time

Measuring customer health isn't a one-time thing. Build a workflow that regularly calls `get_health_score` and logs the result using `list_events`. Mastra AI ensures these checks run on schedule, even if external services are flaky. Furthermore, you can use the tool to check general analytics summaries (`get_analytics_summary`) as part of an automated reporting cycle. The workflow handles retries until it gets a clean report.

Setup guide

Set up Zengain MCP in Mastra AI

Prerequisites

Node.js 18+ and a TypeScript project
@mastra/mcp + @mastra/core packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run npm install @mastra/mcp @mastra/core plus your preferred model provider (e.g. @ai-sdk/openai).
2

Configure the MCPClient
Create an MCPClient with your Vinkius endpoint as a URL object. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and inject tools
Call mcpClient.listTools() and spread the result into your agent's tools object. All Zengain tools become native Mastra tools.
4

Run with any model
Swap openai("gpt-4o") for any AI SDK-compatible provider. Call agent.generate() and the agent routes tool calls through MCP automatically.

agent.ts

import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";

const mcpClient = new MCPClient({
  id: "zengain-mcp-client",
  servers: {
    "zengain-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "Zengain Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to Zengain tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent Zengain transactions"
);
console.log(result.text);

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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.

Why Choose Vinkius

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Common questions about Zengain MCP in Mastra AI

Zengain's tools act as the functional nodes in your complex workflow. The agent can execute `get_analytics_summary` or query user details, and Mastra manages the dependencies between those calls.

It touches all core business data: product inventory (`list_products`), user accounts (`list_users`), conversion metrics (`get_health_score`), and webhooks configuration.

Yes. You can set up a workflow that runs periodically, calling `list_events` to check for high-intent visitor patterns and then notifying an administrator if certain thresholds are crossed.

Absolutely. Mastra AI is built specifically for reliability. It includes automatic retries with exponential backoff, meaning temporary network hiccups won't break your entire process.

While there isn't an explicit 'update' tool listed, you can build a workflow that reads the current state using `get_user_details` and then uses `track_event` to log the change or action taken.

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