How to Use the Azure Service Bus Topic MCP in OpenAI Agents SDK

Q: Can I use custom properties with an Azure Service Bus Topic in OpenAI Agents SDK?

Absolutely. You include a JSON object in the publishmessage call, and the server translates those into standard bus headers.

Push cloud events directly from your OpenAI Agents SDK workflow to Azure Service Bus Topics.

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Connect Azure Service Bus Topic MCP to OpenAI Agents SDK

Create your Vinkius account to connect Azure Service Bus Topic 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 Azure Service Bus Topic with OpenAI Agents SDK

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Direct message publishing for OpenAI Agents SDK

Your agent pushes events straight to your bus without writing custom network code. It maps your agent's output directly into the `publish_message` tool. This setup removes the need for middleman services. You get a direct line from your agent logic to your cloud infrastructure.

Metadata-driven routing

You control how your messages travel by injecting routing info through `publish_message`. Your agent attaches customProperties to dictate subscription paths. This keeps your event logic clean. You define the destination metadata inside the tool call rather than hardcoding it in your agent.

Production-ready event triggers

This MCP server integrates into your existing agent lifecycle. Since the OpenAI Agents SDK manages tool discovery, your code stays lightweight. It treats the bus as a native extension of your agent. You trigger downstream business processes the moment your agent finishes its task.

Setup guide

Set up Azure Service Bus Topic 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 Azure Service Bus Topic tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Azure Service Bus Topic 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="Azure Service Bus Topic Agent",
            instructions="You have access to Azure Service Bus Topic 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 Azure Service Bus Topic MCP in OpenAI Agents SDK

You pass the server URL to the MCPServerStreamableHttp class within your agent setup. Once defined, the tools appear automatically in your agent's available functions.

Yes. Because the agent validates tool inputs before execution, the metadata you pass to `publish_message` stays within your defined safety constraints.

Absolutely. You include a JSON object in the `publish_message` call, and the server translates those into standard bus headers.

Vinkius handles the transport security. You only need to provide an endpoint token, and the traffic stays scoped to your specific server instance.

The server only processes the raw message payload and routing metadata you send. It doesn't store your bus credentials or message history.

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OpenAI Agents SDK sdk-python