How to Use the Azure Log Analytics Workspace MCP in Google ADK

Q: Can I use the Azure Log Analytics Workspace MCP server with Google ADK on Google Cloud?

Yes, you can run this MCP server by configuring McpToolset with your Vinkius endpoint URL. This lets your Gemini-powered agents query Azure logs and combine that data with Vertex AI or BigQuery resources.

Q: How is my Azure Log Analytics Workspace log telemetry protected?

All log telemetry processed by the querylogs tool is transmitted over encrypted channels. Vinkius executes the server inside a zero-trust, ephemeral V8 isolate, ensuring your log data never persists outside of active agent execution.

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Connect Azure Log Analytics Workspace MCP to Google ADK

Create your Vinkius account to connect Azure Log Analytics Workspace to Google ADK 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 Log Analytics Workspace with Google ADK

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Enterprise Log Analysis via Google ADK

Connect Gemini's massive context window directly to your telemetry. Your enterprise agents can now call `query_logs` to fetch thousands of log lines and analyze them in a single reasoning step. This is built specifically for teams running their agent workloads on Google Cloud. The setup uses `McpToolset` with your Vinkius HTTP endpoint. Because Google ADK integrates natively with BigQuery and Vertex AI, your agent can query Azure logs and immediately cross-reference them with Google Cloud data.

Restricted Tool Exposure for Gemini Agents

You don't always want your agent to have full access to every tool. Google ADK lets you use an optional tool names filter to restrict exactly what the agent can see. This means you can expose only the `query_logs` tool to your monitoring agent, keeping your attack surface small. This MCP server handles the Azure authentication on the Vinkius side, so your Google ADK code never touches Azure credentials. Your agent simply sends KQL operations, and the server returns the raw log payload.

Long-Context Azure Log Analysis

Traditional agents choke on large log outputs, but Gemini handles millions of tokens. By calling `query_logs`, your Google ADK agent can ingest massive chunks of historical log data. This lets the agent spot long-term patterns that shorter-context models miss. To implement this, install `google-adk` and configure the `StreamableHttpServerParameters` pointing to your Vinkius endpoint. This MCP setup lets Gemini run complex KQL operations directly against your workspace.

Setup guide

Set up Azure Log Analytics Workspace 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 Log Analytics Workspace 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 Log Analytics Workspace_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Azure Log Analytics Workspace tools via MCP.",
    tools=mcp_tools,
)

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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 Log Analytics Workspace. 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 Log Analytics Workspace MCP in Google ADK

Yes, you can run this MCP server by configuring `McpToolset` with your Vinkius endpoint URL. This lets your Gemini-powered agents query Azure logs and combine that data with Vertex AI or BigQuery resources.

You can use the optional tool names filter in the Google ADK toolset configuration. This allows you to expose only the `query_logs` tool to specific agents while hiding other capabilities.

The server supports both Stdio and Streamable HTTP transports. When deploying Google ADK agents in cloud environments, using the Streamable HTTP transport with your Vinkius endpoint is the easiest way to connect.

No, your agent should only write the operational KQL commands, such as filters or limits. The MCP server automatically prepends the correct, authorized table name before executing the query.

All log telemetry processed by the `query_logs` tool is transmitted over encrypted channels. Vinkius executes the server inside a zero-trust, ephemeral V8 isolate, ensuring your log data never persists outside of active agent execution.

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