How to Use the Azure Service Bus Queue MCP in Google ADK

Q: How do I configure my Google ADK agent with this Azure Service Bus Queue toolset?

Initialize McpToolset with StreamableHttpServerParameters pointing to your Vinkius URL. Pass this toolset into the tools list of your LlmAgent to let Gemini call the pull and acknowledge functions.

Build enterprise-grade Google ADK agents that pull and process Azure Service Bus Queue tasks directly into Gemini.

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Connect Azure Service Bus Queue MCP to Google ADK

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Setup Azure Service Bus Queue with Google ADK

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Feeding queue payloads directly into Google ADK context

Use Gemini's massive token window to process complex, data-heavy Azure messages. Your Google ADK agent calls `pull_message` to grab a pending message and can analyze it alongside giant datasets pulled from BigQuery. This setup works perfectly for enterprise pipelines. The agent reads the queue item, runs deep reasoning across your Google Cloud infrastructure, and then decides how to act.

Reliable queue state management with Gemini reasoning

When your Google ADK agent pulls a message, the item is locked. To remove it permanently, the agent must trigger `acknowledge_message` with the messageId and lockToken. If the Gemini model determines that the message data is corrupted or requires manual intervention, it can choose not to acknowledge it. The lock times out, and the message safely returns to your Azure Service Bus Queue.

Restricting tool exposure in enterprise MCP Server deployments

You don't have to expose every tool to every agent. When configuring your `McpToolset` in Google ADK, you can filter the tool list to only expose `pull_message` to your ingest agents. This limits the blast radius of your AI workers. Your processing agents only get access to `acknowledge_message` when they are explicitly tasked with finishing a job.

Setup guide

Set up Azure Service Bus Queue MCP in Google ADK

Prerequisites

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

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Azure Service Bus Queue tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Azure Service Bus Queue_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Azure Service Bus Queue tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Azure Service Bus Queue MCP in Google ADK

Initialize `McpToolset` with `StreamableHttpServerParameters` pointing to your Vinkius URL. Pass this toolset into the `tools` list of your `LlmAgent` to let Gemini call the pull and acknowledge functions.

Absolutely. Gemini's million-token context window in the Google ADK framework makes it easy to process massive, nested JSON payloads or text files pulled via the `pull_message` tool without running out of memory.

Yes, the ADK supports both Stdio and HTTP transports. For hosted Vinkius deployments, you will use the Streamable HTTP transport to securely connect your Google ADK agent to the MCP Server.

If your agent takes longer to process the message than the lock duration, the message becomes visible to other workers. Make sure to tune your MCP timeout to match your Gemini processing times.

Your message payloads and lock tokens are streamed directly to your Google ADK runtime over a secure, ephemeral connection. Vinkius never caches or stores your queue contents, maintaining strict enterprise data isolation with this MCP Server.

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