How to Use the Azure Service Bus Topic MCP in CrewAI

Q: How do I configure Azure Service Bus Topic in CrewAI?

Add the Vinkius endpoint URL to the mcps list when defining your agent. Make sure you have installed the crewaitools package first.

Q: Does the Azure Service Bus Topic tool support custom routing headers in CrewAI?

Yes. The tool accepts a customProperties JSON object. Your agent can dynamically generate these headers based on the context of the task it just completed.

Give your CrewAI agents the ability to publish events to an Azure Service Bus Topic during autonomous operations.

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Connect Azure Service Bus Topic MCP to CrewAI

Create your Vinkius account to connect Azure Service Bus Topic 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 Azure Service Bus Topic with CrewAI

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Connect CrewAI to Azure Service Bus Topic

The `publish_message` tool lets your autonomous teams poke external systems. A research agent gathers data, an analysis agent formats it, and a dispatcher agent pushes the final result to your cloud queue. Drop the Vinkius URL directly into the `mcps` array of your target agent. The framework automatically exposes the publishing capability to that specific role, keeping other agents focused on their own tasks.

Restrict Publishing to Specific Agents

You don't want every agent in your crew talking to the messaging bus. Using `MCPServerHTTP` and a `tool_filter`, you restrict the `publish_message` tool to your designated moderator or output agent. This prevents hallucinating research agents from accidentally spamming your production topics. The specialized agent receives the payload from its peers, constructs the `customProperties` JSON, and handles the actual transmission through the MCP Server.

Escalate Issues to Cloud Workers

Crews monitor systems and trigger external responses entirely on their own. When a monitor agent detects an anomaly, it passes the context to a response agent. That response agent uses the MCP Server to fire an event into Azure. Downstream logic apps or background workers pick up the message and execute the fix, entirely driven by the initial agent's decision.

Setup guide

Set up Azure Service Bus Topic 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 Azure Service Bus Topic tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Azure Service Bus Topic 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="Azure Service Bus Topic Analyst",
        goal="Access and analyze Azure Service Bus Topic data via MCP.",
        backstory="Expert analyst with direct Azure Service Bus Topic access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Azure Service Bus Topic 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 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 CrewAI

Add the Vinkius endpoint URL to the `mcps` list when defining your agent. Make sure you have installed the `crewai[tools]` package first.

Yes, but it is better practice to assign the MCP Server to a single specialized agent. Have your other agents pass their output to this dispatcher agent to manage the actual publishing.

Yes. The tool accepts a `customProperties` JSON object. Your agent can dynamically generate these headers based on the context of the task it just completed.

CrewAI supports stdio, SSE, and Streamable HTTP. For Vinkius-hosted remote servers, it defaults to HTTP transports to communicate with the endpoint.

Nobody. The message strings and custom JSON properties hit a secure V8 isolate that exists solely for the duration of that single tool call. The execution environment is destroyed immediately, ensuring strict data privacy for your autonomous operations.

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