How to Use the Axle MCP in OpenAI Agents SDK

Directly manage your fleet logistics inside OpenAI Agents SDK with zero configuration.

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Connect Axle MCP to OpenAI Agents SDK

Create your Vinkius account to connect Axle to OpenAI Agents SDK 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 Axle with OpenAI Agents SDK

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Manage your drivers with OpenAI Agents SDK

Call `get_driver` or `list_drivers` to pull live profiles into your agent memory. You get exact duty status updates through `update_driver_status` without leaving your Python environment. Your agents validate every action against the Axle system before committing changes. This keeps your records clean while your agent handles the heavy lifting.

Track your cargo via MCP Server tools

Pull load specifics with `get_load` or scan your entire backlog using `list_loads`. You can push updates to shipments instantly by invoking `update_load` from your agent logic. This MCP Server provides the raw data your agent needs to make routing decisions. It handles the API handshake so you focus on the logic.

Monitor vehicle activity in real time

Use `get_vehicle_location` to see exactly where your assets are. Pair this with `get_vehicle` to check mechanical status or model specifications. Your agent can now react to delays as they happen. It turns static data into active fleet oversight without manual intervention.

Setup guide

Set up Axle MCP in OpenAI Agents SDK

Prerequisites

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

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Axle tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Axle tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Axle tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="Axle Agent",
            instructions="You have access to Axle tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about Axle MCP in OpenAI Agents SDK

You instantiate the MCPServerStreamableHttp class with your Vinkius endpoint. Pass that instance into your agent constructor to let the SDK discover all twelve tools automatically.

Yes. Since the tools return structured data, your guardrails can inspect the output of `get_driver_availability` or `list_documents` before your agent makes a final decision.

Absolutely, as long as you provide the right credentials. Your agent can trigger `update_load` or `update_driver_status` based on external events you feed into the system.

Data stays within your execution environment. The server acts as a pipe, moving GPS coordinates and driver logs directly into your agent's context window.

Vinkius handles the transport security. The server only exposes the specific load and driver records you explicitly request, ensuring your private logistics data isn't exposed elsewhere.

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