How to Use the Kandji MCP in CrewAI

Q: Can CrewAI agents perform bulk Kandji audits?

Yes. You can configure a research agent to call listdevices and pass the results to an analyst agent. They work together to process your entire inventory.

Deploy autonomous agent crews to monitor your Apple fleet using the Kandji MCP Server.

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Connect Kandji MCP to CrewAI

Create your Vinkius account to connect Kandji to CrewAI 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 CrewAI

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Assign specialized agents for Kandji

Set up a monitor agent that uses `get_device` to check specific assets while a moderator agent manages the overall fleet. This specialization makes your operations more efficient. Each agent focuses on one task. One handles the discovery, the other handles the interpretation of the results.

Run autonomous audits with CrewAI

Create a sequential execution flow that uses `list_activity` to summarize recent changes. Your agents report back on what changed in your MDM environment. This gives you a clear summary of your fleet's health. You don't have to read through raw logs anymore.

Manage policies via CrewAI agents

Use `list_parameters` to let your agents compare current security settings against your baseline. They can alert you if a configuration drifts. This turns your security policy into a living check. The agents verify compliance in the background without needing your input.

Setup guide

Set up Kandji MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Kandji tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Kandji Analyst",
    goal="Access and analyze Kandji data via MCP.",
    backstory="Expert analyst with direct Kandji access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Kandji transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Kandji Analyst",
        goal="Access and analyze Kandji data via MCP.",
        backstory="Expert analyst with direct Kandji access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Kandji transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

Get your connection token →

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 CrewAI

Pass the Kandji server URL directly into your agent's mcps list. The agents will automatically discover the tools and start using them based on your instructions.

Yes. You can configure a research agent to call `list_devices` and pass the results to an analyst agent. They work together to process your entire inventory.

The connection is authenticated and scoped to your specific endpoint. Your private device information stays within the secure session of your agent execution.

The server manages the connection, but you should set your agent's task frequency to avoid flooding the API. It keeps your MDM integration stable.

The server provides basic user-to-device mapping. This data is handled as a temporary memory object for the agent's current task and is cleared afterward.

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