How to Use the Zenedu MCP in Mastra AI

Q: How does Zenedu help with reliable messaging data using Mastra AI?

You embed the listbots tool into a workflow. If your initial attempt to list bots fails, Mastra AI automatically retries the connection until it succeeds or hits the maximum retry limit.

Q: Can I track orders using Zenedu with Mastra AI?

Yes. You create a dedicated workflow that calls listbotorders. This ensures that even if initial data retrieval fails, the agent will systematically retry getting the order list.

Q: What happens when I need to check bot subscribers using Zenedu with Mastra AI?

You set up a workflow where the first step is calling listbotsubscribers. If that call succeeds, the agent proceeds to the next conditional step, like checking product availability.

Q: Is Zenedu good for listing funnels with Mastra AI?

It’s great. You wrap listbotfunnels in a workflow that requires tool approval before execution, letting a human check the funnel map output before continuing any subsequent steps.

Q: What specific type of data does Zenedu touch when managing bots with Mastra AI?

Mastra AI handles core operational data like bot names (listbots), subscriber contact information, and funnel definitions using listbotfunnels.

Building Reliable Bot Workflows with Mastra AI and Zenedu's Messaging Tools.

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Connect Zenedu MCP to Mastra AI

Create your Vinkius account to connect Zenedu 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 Zenedu with Mastra AI

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Manage All Bot Assets in Complex Workflows

You can build a workflow that checks for bot existence first. Start by running `list_bots` to confirm the service is up. If it fails, the agent retries with exponential backoff before notifying an admin. This reliability means your multi-step process won't break over transient network issues.

Automate Subscriber and Order Retrieval

Need to audit user data? Run `list_bot_subscribers` followed by `list_bot_orders`. Mastra AI handles the dependency: it only tries to pull orders if subscribers exist. The agent structure manages this conditional branching for you. It's ideal for compliance workflows that must verify both user identity and transaction history.

Verify Product Catalog Status

Use the workflow engine to fetch all products via `list_bot_products` and then cross-reference them with available funnels using `list_bot_funnels`. The system can validate that every product has an associated funnel. This ensures your bot's content is always consistent across its various selling points.

Setup guide

Set up Zenedu 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 Zenedu 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: "zenedu-mcp-client",
  servers: {
    "zenedu-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

const result = await agent.generate(
  "List recent Zenedu 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 Zenedu. 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 Zenedu MCP in Mastra AI

You embed the `list_bots` tool into a workflow. If your initial attempt to list bots fails, Mastra AI automatically retries the connection until it succeeds or hits the maximum retry limit.

Yes. You create a dedicated workflow that calls `list_bot_orders`. This ensures that even if initial data retrieval fails, the agent will systematically retry getting the order list.

You set up a workflow where the first step is calling `list_bot_subscribers`. If that call succeeds, the agent proceeds to the next conditional step, like checking product availability.

It’s great. You wrap `list_bot_funnels` in a workflow that requires tool approval before execution, letting a human check the funnel map output before continuing any subsequent steps.

Mastra AI handles core operational data like bot names (`list_bots`), subscriber contact information, and funnel definitions using `list_bot_funnels`.

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