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 | 55 security tools | Wazuh 4.8.0–4.14.7 |
Changelog
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.
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.