How to Use the Azure Service Bus Topic MCP in AutoGen

Q: How do I hook up an Azure Service Bus Topic to AutoGen?

Use the autogen-extmcp package. Fetch the tools via HTTP parameters and pass the list directly to any agent that needs publishing rights.

Q: How do AutoGen agents format the routing metadata for an Azure Service Bus Topic?

The swarm generates a JSON object for the customProperties parameter. They will format it according to the instructions you provide in their system prompts.

Let your AutoGen swarms debate and publish events via this MCP Server.

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Connect Azure Service Bus Topic MCP to AutoGen

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Setup Azure Service Bus Topic with AutoGen

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Single agents make mistakes. AutoGen lets you build a system where a primary agent drafts a message, a critic reviews it, and they debate until both agree. Once consensus hits, they call this MCP tool to push the validated payload to your Azure Service Bus Topic. This prevents rogue AI actions in production environments. You get the speed of automated event generation with the safety of multi-perspective validation. The `publish_message` tool only fires when the entire swarm signs off on the payload.

Negotiated routing metadata

Event routing requires strict adherence to schemas. Your agents can argue over exactly which tags belong in the `customProperties` JSON object. A security agent might demand a high-priority flag, while a cost-control agent pushes for standard processing. They resolve the conflict before hitting the API. The winning metadata goes into the publish command, ensuring downstream Azure subscriptions route the event exactly where it needs to go based on the swarm's logic.

Zero-friction tool distribution

Setting up tools across a swarm usually involves a mess of custom adapters. With Vinkius, you pass the endpoint URL to `mcp_server_tools` using `StreamableHttpServerParams` for your MCP setup. AutoGen's internal adapter handles the schema conversion automatically. You just hand the resulting tool list to your `AssistantAgent` constructor. Vinkius manages the Azure auth and executes the requests in an ephemeral V8 Isolate Sandbox. Your agents focus purely on the conversation.

Setup guide

Set up Azure Service Bus Topic MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Azure Service Bus Topic tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

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

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Azure Service Bus Topic_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Azure Service Bus Topic data")
print(result.messages[-1].content)

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Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

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

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Azure Service Bus Topic_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Azure Service Bus Topic data")
    print(result.messages[-1].content)

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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 Azure Service Bus Topic. 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 Azure Service Bus Topic MCP in AutoGen

Use the `autogen-ext[mcp]` package. Fetch the tools via HTTP parameters and pass the list directly to any agent that needs publishing rights.

Yes. You can provide the tool to a specific execution agent, or give it to multiple agents and let them decide who handles the actual publishing step.

The swarm generates a JSON object for the `customProperties` parameter. They will format it according to the instructions you provide in their system prompts.

The error feeds right back into the chat. The agents will read the failure reason, discuss what went wrong, fix the payload, and try again.

Your message payloads and routing tags are shielded by a zero-trust architecture. Vinkius spins up an isolated, ephemeral sandbox just to execute the publish command, leaving no trace of your internal agent discussions behind.

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