How to Use the IBM QRadar MCP in Google ADK

Q: Can I use Google ADK to run AQL queries on IBM QRadar?

Yes, the server exposes executeaql as a native tool. Your agent triggers the search, monitors the status, and retrieves the results upon completion.

Q: How do I update IBM QRadar offenses from Google ADK?

Your agent uses the updateoffense tool to modify the state of an incident. You can build automation flows that close false positives or assign tickets to your team.

Integrate IBM QRadar with Google ADK to turn your security logs into actionable intelligence for your Gemini-powered agents.

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Connect IBM QRadar MCP to Google ADK

Create your Vinkius account to connect IBM QRadar 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 IBM QRadar with Google ADK

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Direct offense investigation

Your agent queries `get_offenses` to monitor your SOC queue in real time. It identifies high-severity issues before your analysts even see them. After spotting an incident, the agent runs `get_offense_details` to extract the relevant indicators. It gathers the facts so you can focus on the response strategy.

Execute deep AQL analysis

Use your agent to run `execute_aql` queries against your full log history. It parses complex security data without manual query construction. By chaining `get_aql_status` and `get_aql_results`, the agent handles the heavy lifting of long-running searches. You get the insights you need without timing out.

Context-aware security monitoring

The agent pulls your `get_network_hierarchy` and `get_log_sources` to ensure every alert is properly attributed. It knows exactly which segment of your network is under pressure. It verifies activity against `get_rules` and `get_reference_sets` for instant correlation. This turns raw logs into a clear understanding of your current security posture.

Setup guide

Set up IBM QRadar 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 IBM QRadar 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="IBM QRadar_agent",
    model="gemini-2.0-flash",
    instruction="You have access to IBM QRadar 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 IBM QRadar. 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 IBM QRadar MCP in Google ADK

You pass the MCP toolset to your LlmAgent configuration. The agent then calls `get_offenses` whenever it needs to inspect your current security queue.

Yes, the server exposes `execute_aql` as a native tool. Your agent triggers the search, monitors the status, and retrieves the results upon completion.

Your agent uses the `update_offense` tool to modify the state of an incident. You can build automation flows that close false positives or assign tickets to your team.

No, the server runs on Vinkius infrastructure. You just point your Google ADK client to the provided endpoint to start interacting with your security data.

The connection uses a zero-trust architecture. Your QRadar data is accessed only via authenticated requests, and the server does not store your sensitive logs or offense history.

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