Wazuh MCP Server

Overview

The Wazuh MCP Server is a Rust‑based bridge that lets Claude and other Model Context Protocol (MCP) clients pull real‑time security data from a Wazuh SIEM without writing custom API integrations. It translates the rich, but often verbose, Wazuh REST responses into concise MCP resources, tools and prompts that can be queried with natural language. Developers building AI‑powered security tooling no longer need to understand Wazuh’s query syntax or paginate through large JSON payloads; instead they can ask questions like “Show me the critical vulnerabilities on our web servers” or “Which processes are running on agent 001?” and receive structured, actionable answers.

Why it matters for AI assistants

Modern security operations demand rapid situational awareness. An AI assistant that can surface alerts, agent health, vulnerability status and compliance checks on demand becomes a first‑line analyst. The Wazuh MCP Server removes the friction of manual API calls, pagination, and data wrangling, enabling developers to embed real‑time security context directly into chat flows, dashboards or automated playbooks. This tight coupling means that the assistant can recommend remediation steps, generate compliance evidence or trigger incident response workflows—all from a single conversational interface.

Key capabilities

• Alert and event access – Fetch summaries, details or trends for security alerts across the indexer.
• Agent management – Retrieve health status, running processes, open ports and network services for any agent.
• Vulnerability data – Pull critical or all vulnerability summaries, filter by host or severity.
• Rule and configuration insight – Inspect detection rule effectiveness and compliance with PCI‑DSS, HIPAA, SOX or GDPR.
• Operational metrics – Monitor cluster health, weekly statistics and log‑collector performance to keep the SIEM running smoothly.
• Forensic support – Search logs and event data for incident investigation or audit reporting.

Real‑world use cases

1. Security alert triage – Analysts can ask the assistant to list high‑severity alerts, then drill down into the underlying events without leaving the chat.
2. Vulnerability prioritization – Compliance teams can request a list of critical vulnerabilities per host, enabling targeted patching and risk management.
3. Agent health monitoring – DevOps can query which agents are offline or misconfigured, ensuring full coverage before a breach occurs.
4. Rule optimization – Security engineers can review rule hit rates and adjust detection logic directly from the AI interface.
5. Incident response automation – A chatbot can trigger automated playbooks based on the current alert landscape, speeding up containment and remediation.

Integration into AI workflows

The server exposes its functionality through MCP resources that map naturally to conversational intents. Developers define prompts such as “Get Wazuh alert summary” and bind them to the corresponding tool. When an AI assistant receives a user query, it resolves the intent, calls the MCP tool, and presents the structured result in a human‑readable format. Because all data is already pre‑formatted, no additional parsing logic is required on the client side.

Unique advantages

• Zero‑code integration – No need to write custom adapters or handle pagination; the server does it for you.
• High performance – Rust implementation ensures low latency responses, even when querying large SIEM datasets.
• Extensibility – New Wazuh endpoints can be added as additional tools without changing the client logic.
• Compliance‑ready – Built‑in prompts for regulatory frameworks make it straightforward to generate audit evidence.

In summary, the Wazuh MCP Server transforms a complex SIEM into an AI‑friendly data source, empowering developers to deliver instant, contextual security intelligence through conversational agents.