Kandji MCP Server for OpenAI Agents SDK 10 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Kandji through the Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails — no manual schema definitions required.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
async with MCPServerStreamableHttp(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
) as mcp_server:
agent = Agent(
name="Kandji Assistant",
instructions=(
"You help users interact with Kandji. "
"You have access to 10 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from Kandji"
)
print(result.final_output)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Kandji MCP Server
Empower your AI agents with Kandji's modern Apple MDM platform. This MCP server allows you to list and retrieve device details, manage blueprints and custom apps, track administrative activity, and view system security parameters directly through the Kandji API. Ideal for automating IT operations and fleet security for macOS and iOS.
The OpenAI Agents SDK auto-discovers all 10 tools from Kandji through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns — chain multiple agents where one queries Kandji, another analyzes results, and a third generates reports, all orchestrated through the Vinkius.
The Kandji MCP Server exposes 10 tools through the Vinkius. Connect it to OpenAI Agents SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Kandji to OpenAI Agents SDK via MCP
Follow these steps to integrate the Kandji MCP Server with OpenAI Agents SDK.
Install the SDK
Run pip install openai-agents in your Python environment
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
Run the script
Save the code above and run it: python agent.py
Explore tools
The agent will automatically discover 10 tools from Kandji
Why Use OpenAI Agents SDK with the Kandji MCP Server
OpenAI Agents SDK provides unique advantages when paired with Kandji through the Model Context Protocol.
Native MCP integration via `MCPServerSse` — pass the URL and the SDK auto-discovers all tools with full type safety
Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure
Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate
First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output
Kandji + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the Kandji MCP Server delivers measurable value.
Automated workflows: build agents that query Kandji, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents — one queries Kandji, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through Kandji tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query Kandji to resolve tickets, look up records, and update statuses without human intervention
Kandji MCP Tools for OpenAI Agents SDK (10)
These 10 tools become available when you connect Kandji to OpenAI Agents SDK via MCP:
get_device
Essential for deep-dive auditing of a specific asset. Retrieves details for a specific device
get_organization
Use to verify account identity. Retrieves details about your Kandji organization
list_activity
Essential for auditing system changes and recent management history. Lists recent management activity
list_auto_apps
Essential for auditing standard software libraries. Lists all Kandji Auto Apps
list_blueprints
Useful for understanding how devices are categorized and configured. Lists all device blueprints
list_commands
g., Lock, Wipe, Restart) sent to managed devices. Useful for auditing remote actions. Lists recent MDM commands sent to devices
list_custom_apps
Useful for auditing non-store software deployments. Lists all custom applications
list_devices
Returns device names, IDs, and OS versions. Use this as the main tool for auditing the device fleet. Lists all managed Apple devices in Kandji
list_parameters
Useful for auditing available security controls. Lists all library parameters (policies)
list_users
Useful for identifying device owners and primary users. Lists all users associated with devices
Example Prompts for Kandji in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Kandji immediately.
"List all managed Mac computers in Kandji."
"Show me the details for device ID 'abc-123'."
"Check recent administrative activity in Kandji."
Troubleshooting Kandji MCP Server with OpenAI Agents SDK
Common issues when connecting Kandji to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
Kandji + OpenAI Agents SDK FAQ
Common questions about integrating Kandji MCP Server with OpenAI Agents SDK.
How does the OpenAI Agents SDK connect to MCP?
MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.Can I use multiple MCP servers in one agent?
MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.Does the SDK support streaming responses?
Connect Kandji with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Kandji to OpenAI Agents SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.