Wazuh MCP Server
About
AI-powered security operations for Wazuh SIEM—use any MCP-compatible client to ask security questions in plain English. Faster threat detection, incident triage, and compliance checks with real-time monitoring and anomaly spotting. Production-ready MCP server for conversational S
Details
- Author
- unmuktoai
- GitHub stars
- 198
- Downloads
- 660
- Categories
- Developer Tools, AI
Jump to
- 54 security tools across alerts, agents, vulnerabilities, compliance, and active response
- Works with cloud LLMs (Claude, GPT) and local LLMs (Llama, Qwen)
- Fully air-gappable — data never leaves your network with local mode
- RBAC with opt-in wazuh:write scope for state‑changing tools
- Audit logging for every destructive action
- Rate limiting, circuit breakers, and input validation
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Wazuh MCP ServerCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Deploy with Docker Compose, configure WAZUH_HOST, WAZUH_USER, and WAZUH_PASS in .env, then connect any MCP-compliant client (Claude Desktop, Open WebUI, mcphost) to the /mcp endpoint. Quick start: git clone, cp .env.example .env, edit, docker compose up -d. For local LLMs, use mcphost with --model ollama/qwen2.5:7b. For multi-user SOC, add as an MCP tool server in Open WebUI Admin Settings.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"wazuh mcp server": {
"Wazuh-MCP-Server": {
"command": "docker",
"args": [
"compose",
"up",
"-d"
]
}
}
}
}McpServers
{
"Wazuh-MCP-Server": {
"command": "docker",
"args": [
"compose",
"up",
"-d"
]
}
}Wazuh MCP Server
Talk to your SIEM. Query alerts, hunt threats, check vulnerabilities, and trigger active responses across your entire Wazuh deployment — through natural conversation with any AI assistant.
> v4.2.1 | 54 security tools | Wazuh 4.8.0–4.14.4 | Changelog
---
What This Does
Your Wazuh SIEM generates thousands of alerts, vulnerability findings, and agent events daily. Investigating them means juggling dashboards, writing API queries, and manually correlating data across tools.
This MCP server turns that workflow into a conversation:
You: "Show me critical alerts from the last hour"
AI: [calls get_wazuh_alerts] Found 3 critical alerts:
1. SSH brute force from 10.0.1.45 → agent-003 (Rule 5712, Level 10)
2. Rootkit detection on agent-007 (Rule 510, Level 12)
3. FIM change /etc/shadow on agent-001 (Rule 550, Level 10)
You: "Block that source IP on agent-003"
AI: [calls wazuh_block_ip] Blocked 10.0.1.45 via firewall-drop on agent-003.
You: "Which agents have unpatched critical CVEs?"
AI: [calls get_wazuh_critical_vulnerabilities] 3 agents with critical vulnerabilities...
It works with Claude Desktop, Open WebUI + Ollama (fully local, air-gapped), mcphost, or any MCP-compliant client.
---
Works With Cloud AND Local LLMs
This is a standard MCP tool server. It doesn't care what LLM you use — it just executes tools and returns results.
| Mode | LLM | Client | Data leaves your network? |
|------|-----|--------|--------------------------|
| Cloud | Claude, GPT, etc. | Claude Desktop, any MCP client | Yes (to LLM provider) |
| Local | Llama, Qwen, Mistral via Ollama | Open WebUI, mcphost, IBM/mcp-cli | No. Fully air-gappable. |
For security teams that can't send SIEM data to cloud APIs (compliance, air-gapped networks, data sovereignty), the local mode with Ollama keeps everything on-premises. Both modes coexist — same server, same tools, same API.
Quick Start: Local LLM with mcphost
```bash
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