How to Use the Kandji MCP in Mastra AI

Q: Are Kandji organization details accessible in Mastra AI?

Use getorganization to verify your environment context before running bulk operations. It ensures your agent is targeting the right tenant.

Automate your MDM workflows in Mastra AI by chaining Kandji tools for complex fleet management tasks.

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Connect Kandji MCP to Mastra AI

Create your Vinkius account to connect Kandji 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 Kandji with Mastra AI

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Build automated device workflows

Combine `list_blueprints` and `list_devices` to create agents that verify compliance across your fleet. Your agents can identify out-of-sync machines and flag them for attention. This reduces manual audit time. You write the logic once, and the agent handles the comparison against your desired state.

Coordinate complex Mastra AI actions

Use `list_commands` within your workflows to verify previous actions before executing new ones. This prevents accidental duplicate commands. It adds a layer of safety to your automation. The agent checks the history before it attempts to push a new configuration.

Automate app inventory checks

Query `list_auto_apps` and `list_custom_apps` to ensure your software libraries match requirements. If an app is missing, the agent triggers a notification. This keeps your software deployment clean. You don't have to watch the dashboard manually; the agent scans the environment for you.

Setup guide

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

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

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

You instantiate the MCP client in your Mastra config and spread the tools into your agent definitions. This gives your agents direct access to your MDM data.

Yes. You can define conditional logic in your workflows to retry requests if the Kandji API returns a failure. It keeps your automation running smoothly.

Use `get_organization` to verify your environment context before running bulk operations. It ensures your agent is targeting the right tenant.

All communication happens over secure channels via your unique endpoint token. Data is never cached by the server and exists only for the duration of the request.

It provides user names and IDs associated with devices. This information is strictly encrypted in transit and used only for the specific audit task you define.

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