How to Use the ChatGen MCP in Mastra AI

Q: How do I use the ChatGen tools within a Mastra AI agent?

First, you'll instantiate the MCPClient from @mastra/mcp with your server URL. Then, call mcpClient.listTools() and spread the results into your agent's tools property. Mastra AI takes care of the tool invocation from there.

Q: How can Mastra AI and ChatGen automate lead qualification?

You can design a workflow where an agent uses listleads to find new prospects. For each one, it calls getleaddetails and, based on your defined logic, uses data from listteams to route the lead to the correct people.

Q: Is human approval required for deleting a bot?

It can be. Mastra AI supports a requireToolApproval option. If you enable it for the deletebot tool, the workflow will pause and wait for a human to confirm before executing the deletion.

Build resilient, multi-step workflows for ChatGen. Automate lead processing and bot management with Mastra AI's built-in error handling.

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Connect ChatGen MCP to Mastra AI

Create your Vinkius account to connect ChatGen 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 ChatGen with Mastra AI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Reliable Chatbot Automation

This MCP server gives your Mastra agent the tools to manage the full lifecycle of your ChatGen bots. You can build workflows that don't just `create_bot`, but also follow up with `get_bot` to confirm the operation succeeded. Because Mastra AI has automatic retries and conditional logic, you can build truly robust automation. If a bot creation fails, your workflow can automatically try again or trigger a notification, all without you writing complex error-handling code.

Build Complex Lead Funnels with Mastra AI

Automate what happens after a lead is captured. A Mastra AI workflow can periodically run `list_leads`, and for each new prospect, use `get_lead_details` to check their info. This is where Mastra's logic shines. Based on the lead's data, your agent can make decisions. If they're a high-value prospect, the agent can look up the right sales team with `list_teams` and assign it. If not, it can trigger another action. You're building an intelligent, automated sales development representative.

Update Bots Based on Performance

Don't just set up your bots and forget them. With Mastra AI, you can create a workflow that actively monitors and improves them. The workflow can use `list_conversations` to analyze a bot's recent performance. If the workflow detects that a bot's engagement rate has dropped, it can automatically trigger the `update_bot` tool to test a new greeting or a different set of qualifying questions. It’s a self-correcting system for your lead-generation bots.

Setup guide

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

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

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

First, you'll instantiate the `MCPClient` from `@mastra/mcp` with your server URL. Then, call `mcpClient.listTools()` and spread the results into your agent's `tools` property. Mastra AI takes care of the tool invocation from there.

Yes, that's exactly what Mastra AI is designed for. The framework includes automatic retries with exponential backoff. Your workflow simply calls the `create_bot` tool, and Mastra handles any transient failures for you.

You can design a workflow where an agent uses `list_leads` to find new prospects. For each one, it calls `get_lead_details` and, based on your defined logic, uses data from `list_teams` to route the lead to the correct people.

It can be. Mastra AI supports a `requireToolApproval` option. If you enable it for the `delete_bot` tool, the workflow will pause and wait for a human to confirm before executing the deletion.

The server interacts with your ChatGen account's bot settings, captured lead information, and conversation history. Your Vinkius endpoint token authenticates every API call. The server environment is ephemeral, meaning it doesn't store your data after an operation finishes.

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