IBM QRadar MCP Server for OpenAI Agents SDK 10 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect IBM QRadar through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MCPServerStreamableHttp(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
) as mcp_server:
agent = Agent(
name="IBM QRadar Assistant",
instructions=(
"You help users interact with IBM QRadar. "
"You have access to 10 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from IBM QRadar"
)
print(result.final_output)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About IBM QRadar MCP Server
Connect IBM QRadar to any AI agent via MCP.
How to Connect IBM QRadar to OpenAI Agents SDK via MCP
Follow these steps to integrate the IBM QRadar MCP Server with OpenAI Agents SDK.
Install the SDK
Run pip install openai-agents in your Python environment
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
Run the script
Save the code above and run it: python agent.py
Explore tools
The agent will automatically discover 10 tools from IBM QRadar
Why Use OpenAI Agents SDK with the IBM QRadar MCP Server
OpenAI Agents SDK provides unique advantages when paired with IBM QRadar through the Model Context Protocol.
Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety
Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure
Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate
First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output
IBM QRadar + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the IBM QRadar MCP Server delivers measurable value.
Automated workflows: build agents that query IBM QRadar, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents. one queries IBM QRadar, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through IBM QRadar tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query IBM QRadar to resolve tickets, look up records, and update statuses without human intervention
IBM QRadar MCP Tools for OpenAI Agents SDK (10)
These 10 tools become available when you connect IBM QRadar to OpenAI Agents SDK via MCP:
execute_aql
Returns a search ID for async retrieval. Execute an Ariel Query Language (AQL) search
get_aql_results
Get results from a completed AQL search
get_aql_status
Get the status of an AQL search
get_log_sources
List QRadar log sources
get_network_hierarchy
List QRadar network hierarchy
get_offense_details
Get details for a specific QRadar offense
get_offenses
List QRadar offenses
get_reference_sets
). List QRadar reference sets
get_rules
List QRadar correlation rules
update_offense
Update a QRadar offense
Troubleshooting IBM QRadar MCP Server with OpenAI Agents SDK
Common issues when connecting IBM QRadar to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
IBM QRadar + OpenAI Agents SDK FAQ
Common questions about integrating IBM QRadar MCP Server with OpenAI Agents SDK.
How does the OpenAI Agents SDK connect to MCP?
MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.Can I use multiple MCP servers in one agent?
MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.Does the SDK support streaming responses?
Connect IBM QRadar with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect IBM QRadar to OpenAI Agents SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.