How to Use the Kaseya MCP in Mastra AI

Q: Can I use Kaseya groups with Mastra AI agents?

Yes. Use listgroups to define the scope of your agent's work. This ensures your automations only target the intended machine groups.

Build resilient automation workflows for Kaseya using the Mastra AI framework.

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Connect Kaseya MCP to Mastra AI

Create your Vinkius account to connect Kaseya 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 Kaseya with Mastra AI

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Perplexity

Automated Kaseya workflows with Mastra AI

Define complex logic using `list_workflows` to manage your infrastructure state. Mastra AI handles retries and conditional branching if an action fails. This lets you build self-healing systems. If a task hits a snag, the agent automatically retries or alerts your team.

Mastra AI managed agent inventory

Use `list_agents` to maintain an accurate record of your fleet. The framework keeps your asset data synchronized across your entire automation pipeline. Reliable infrastructure management depends on current data. This ensures your agent always acts on the latest device status.

Audit trail visibility in Mastra AI

Integrate `list_audit_logs` to keep a record of every action your agents perform. Mastra AI provides the structure needed to review past operations for compliance. You keep full visibility into what changed and when. It turns raw log data into a clear history of your system's evolution.

Setup guide

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

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

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

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Common questions about Kaseya MCP in Mastra AI

Absolutely. You can use the Mastra AI engine to create conditional paths based on the output of your tools, such as routing a ticket if a script fails.

Mastra AI includes built-in retry logic and exponential backoff. If a connection to your infrastructure drops, the agent waits and tries again automatically.

Every tool call is logged by the framework. You can inspect exactly which Kaseya data points were requested by your agent at any time.

Yes. Use `list_groups` to define the scope of your agent's work. This ensures your automations only target the intended machine groups.

We use scoped tokens for every request. Only the specific machine records required for your workflow are exposed, ensuring your infrastructure credentials remain protected.

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