QRadar MCP Server

QRadar MCP Server

Model Context Protocol (MCP) server for IBM QRadar SIEM - Access 728+ QRadar REST API endpoints through just 4 intelligent MCP tools.

🎯 What is This?

QRadar MCP Server bridges the gap between Large Language Models (LLMs) and IBM QRadar SIEM. It enables natural language interactions with your security data—no need to memorize 728 API endpoints.

The Problem

• QRadar has 728+ REST API endpoints — overwhelming for developers and LLMs alike
• Traditional approach: Define each endpoint as a separate tool → massive token consumption
• Result: Expensive API calls, slow responses, context limits exceeded

The Solution

Instead of exposing 728 tools, we expose just 4 intelligent tools:

Token Efficiency

• 96% reduction in tool definition tokens
• 25x faster LLM processing
• Works with any LLM (Claude, GPT, Gemini, Llama)

Who Should Use This?

• Security analysts wanting natural language QRadar queries
• DevOps teams automating security workflows
• AI developers building QRadar-integrated applications
• SOC teams needing quick incident data access

🌐 Experience It Live

IBM MCP Client (Web UI)

Try the full experience with our React + FastAPI client:

Live Demo: http://9.30.147.112:8000 🚀

Container Registry: ghcr.io/addanuj/ibm-mcp-client:latest

Try: "Show me top 10 offenses", "How many assets?", "Get QRadar version", "List 5 rules"

🏗️ Architecture

graph TB
    subgraph "Client Layer"
        A[MCP Client/LLM] 
    end
    
    subgraph "MCP Server Container"
        B[Python FastAPI Server<br/>Port: 8001]
        C[4 MCP Tools]
        D[QRadar API Wrapper<br/>728 Endpoints]
    end
    
    subgraph "QRadar SIEM"
        E[REST API<br/>v26.0+]
        F[Offenses]
        G[Assets]
        H[Rules]
        I[Ariel Search]
    end
    
    A -->|HTTP/SSE or stdio| B
    B --> C
    C --> D
    D -->|HTTPS REST| E
    E --> F
    E --> G
    E --> H
    E --> I
    
    style A fill:#e1f5ff
    style B fill:#fff3e0
    style C fill:#f3e5f5
    style D fill:#e8f5e9
    style E fill:#fce4ec

📦 What's Inside

4 Intelligent Tools

Supported Endpoints (728 total)

• SIEM: Offenses, sources, destinations
• Assets: Asset model, vulnerabilities, compliance
• Analytics: Rules, building blocks, searches
• Ariel: AQL queries, searches, results
• Reference Data: Sets, maps, collections
• Config: Domains, log sources, users
• System: Health, licensing, servers

🚀 Quick Start

Option 1: Pull from Registry (Run as Container)

# Pull multi-architecture image
docker pull ghcr.io/addanuj/qradar-mcp-server:latest

# Run as container
docker run -d \
  --name qradar-mcp-server \
  -p 8001:8001 \
  -e QRADAR_HOST="https://your-qradar-console.com" \
  -e QRADAR_API_TOKEN="your-sec-token-here" \
  -e QRADAR_VERIFY_SSL="false" \
  ghcr.io/addanuj/qradar-mcp-server:latest \
  --host 0.0.0.0 --port 8001

Option 2: Build from Source (Run as Container)

# Clone repository
git clone https://github.ibm.com/ashrivastava/QRadar-MCP-Server.git
cd QRadar-MCP-Server

# Build container image
docker build -t qradar-mcp-server:latest -f container/Dockerfile .

# Run as container
docker run -d \
  --name qradar-mcp-server \
  -p 8001:8001 \
  -e QRADAR_HOST="https://your-qradar.com" \
  -e QRADAR_API_TOKEN="token" \
  qradar-mcp-server:latest \
  --host 0.0.0.0 --port 8001

Option 3: Local Development (Run as Python Service)

# Install dependencies
pip install -e .

# Set environment variables
export QRADAR_HOST="https://your-qradar.com"
export QRADAR_API_TOKEN="your-token"

# Run in stdio mode (for Claude Desktop)
python -m src.server

# OR run in HTTP mode for local testing
python -m src.server --host 0.0.0.0 --port 8001

🔧 Configuration

Environment Variables

Runtime Modes

HTTP/SSE Mode (Recommended for Containers)

python -m src.server --host 0.0.0.0 --port 8001

• Exposes REST API on port 8001
• Health check: http://localhost:8001/health
• Tools list: http://localhost:8001/tools
• SSE streaming support

stdio Mode (for Claude Desktop)

python -m src.server

• Communicates via stdin/stdout
• Use in Claude Desktop MCP configuration
• No network exposure needed

Usage Examples

Check Server Health

curl http://localhost:8001/health
# Response: {"status":"healthy","mode":"http","tools":4,"endpoints":728}

List Available Tools

curl http://localhost:8001/tools

Call a Tool (Get Offenses)

curl -X POST http://localhost:8001/tools/call \
  -H "Content-Type: application/json" \
  -d '{
    "name": "qradar_get",
    "arguments": {
      "endpoint": "/siem/offenses",
      "limit": 10,
      "qradar_host": "https://your-qradar.com",
      "qradar_token": "your-token"
    }
  }'

Discover Endpoints

curl -X POST http://localhost:8001/tools/call \
  -H "Content-Type: application/json" \
  -d '{
    "name": "qradar_discover",
    "arguments": {
      "search": "offenses",
      "qradar_host": "https://your-qradar.com",
      "qradar_token": "your-token"
    }
  }'

📁 Project Structure

QRadar-MCP-Server/
├── container/
│   └── Dockerfile              # Multi-arch container definition
├── src/
│   ├── __init__.py
│   ├── __main__.py            # Entry point
│   ├── server.py              # FastAPI server (HTTP mode)
│   ├── client.py              # QRadar API client wrapper
│   └── tools.py               # 4 MCP tools with 728 endpoint definitions
└── pyproject.toml             # Python package config

🚦 Supported QRadar Versions

• QRadar 7.3.x ✅ (tested)
• QRadar 7.4.x ✅ (tested)
• QRadar 7.5.x ✅ (tested)

📞 Support

Reporting Issues & Feature Requests

Found a bug?

1. Go to: https://github.ibm.com/ashrivastava/QRadar-MCP-Server/issues
2. Click "New Issue"
3. Provide: clear title, steps to reproduce, QRadar version, and logs (docker logs qradar-mcp-server)

Have a suggestion?

1. Open issue with [Feature Request] prefix
2. Describe use case and expected behavior

Need help?

• Check logs: docker logs qradar-mcp-server
• Search existing issues: https://github.ibm.com/ashrivastava/QRadar-MCP-Server/issues
• Contact: [email protected]

⚠️ Disclaimer

This is a Minimum Viable Product (MVP) for testing and demonstration purposes only.

• NOT for production use
• No warranty or support guarantees
• Use at your own risk
• For production deployments, conduct thorough security review and testing
• IBM is not responsible for any issues arising from the use of this software