Which integrations are available for this server?

Retrieves security alerts from Elasticsearch indices containing Wazuh data, transforming them into standardized MCP messages. Uses Flask to expose an HTTP endpoint for serving transformed security event data to clients.

How do I use Wazuh MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Wazuh MCP Server show me recent critical security alerts from the last hour" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

de en es ja ko ru zh

Wazuh MCP Server

by gensecaihq

Overview Schema Related Servers Score Discussions

Python

Remote

Wazuh MCP Server

License: MIT Python 3.11+ MCP 2025-11-25 Docker

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 | 48 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_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.

Related MCP server: OpenSearch MCP Server

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

# 1. Start the MCP server
docker compose up -d

# 2. Install mcphost (Go binary, no dependencies)
go install github.com/mark3labs/mcphost@latest

# 3. Configure
cat > ~/.mcphost.yml << 'EOF'
mcpServers:
  wazuh:
    type: remote
    url: http://localhost:3000/mcp
    headers: ["Authorization: Bearer ${env://MCP_API_KEY}"]
EOF

# 4. Chat with your SIEM using a local model
export MCP_API_KEY="your-key-from-server-logs"
mcphost --model ollama/qwen2.5:7b

Quick Start: Multi-User SOC with Open WebUI

Open WebUI v0.6.31+ connects to our /mcp endpoint natively. Add it as an MCP tool server in Admin Settings, and your entire team gets AI-powered SIEM analysis with conversation history, RBAC, and a web UI.

48 Security Tools

Every tool is validated, rate-limited, scope-checked, and audit-logged.

Category	Tools	What They Do
Alerts (4)	`get_wazuh_alerts` `get_wazuh_alert_summary` `analyze_alert_patterns` `search_security_events`	Query, filter, search, and analyze alert data via Elasticsearch
Agents (6)	`get_wazuh_agents` `get_wazuh_running_agents` `check_agent_health` `get_agent_processes` `get_agent_ports` `get_agent_configuration`	Monitor agent status, running processes, open ports, and configs
Vulnerabilities (3)	`get_wazuh_vulnerabilities` `get_critical_vulnerabilities` `vulnerability_summary`	Query CVEs by severity, agent, and package
Security Analysis (6)	`analyze_security_threat` `check_ioc_reputation` `perform_risk_assessment` `get_top_security_threats` `generate_security_report` `run_compliance_check`	Threat analysis, IOC lookup, risk scoring, compliance checks
System (10)	`get_wazuh_statistics` `get_wazuh_cluster_health` `get_wazuh_rules_summary` `search_wazuh_manager_logs` ...	Cluster health, rules, manager logs, stats
Active Response (9)	`wazuh_block_ip` `wazuh_isolate_host` `wazuh_kill_process` `wazuh_disable_user` `wazuh_quarantine_file` ...	Block IPs, isolate hosts, kill processes, quarantine files
Verification (5)	`wazuh_check_blocked_ip` `wazuh_check_agent_isolation` `wazuh_check_process` `wazuh_check_user_status` ...	Verify active response actions took effect
Rollback (5)	`wazuh_unisolate_host` `wazuh_enable_user` `wazuh_restore_file` `wazuh_firewall_allow` `wazuh_host_allow`	Undo active response actions

Quick Start

Prerequisites

Docker 20.10+ with Compose v2
Wazuh 4.8.0–4.14.4 with API access enabled

Deploy

git clone https://github.com/gensecaihq/Wazuh-MCP-Server.git
cd Wazuh-MCP-Server
cp .env.example .env

Edit .env:

WAZUH_HOST=your-wazuh-server
WAZUH_USER=your-api-user
WAZUH_PASS=your-api-password

docker compose up -d
curl http://localhost:3000/health

Connect Claude Desktop

Settings → Connectors → Add custom connector
URL: https://your-server/mcp
Add Bearer token in Advanced settings

Detailed setup: Claude Integration Guide

Security

This server sits between an LLM and your SIEM. Security is not optional.

Layer	What It Does
RBAC	Per-tool scope enforcement. 14 active response tools require `wazuh:write`. Read-only tokens can query but never trigger actions. Authless mode is read-only by default.
Audit Logging	Every destructive tool call (block IP, isolate host, kill process) is logged with client ID, session, timestamp, and full arguments.
Output Sanitization	Credentials, tokens, and API keys in alert `full_log` fields are redacted before reaching the LLM. Prevents credential leakage through AI responses.
Input Validation	Every parameter validated: regex agent IDs, `ipaddress` module for IPs, shell metacharacter blocking for active response, Elasticsearch Query DSL (no string interpolation).
Rate Limiting	Per-client sliding window with escalating block duration (10s → 5min).
Circuit Breakers	Wazuh API failures trigger fail-fast for 60s, auto-recover. Single trial in HALF_OPEN state.
Log Sanitization	Global filter redacts passwords, tokens, secrets from all server logs.
Container Hardening	Non-root user, read-only filesystem, `CAP_DROP ALL`, `no-new-privileges`.

# Generate a secure API key
python -c "import secrets; print('wazuh_' + secrets.token_urlsafe(32))"

Configuration

Required

Variable	Description
`WAZUH_HOST`	Wazuh Manager hostname or IP
`WAZUH_USER`	API username
`WAZUH_PASS`	API password

Optional

Variable	Default	Description
`WAZUH_PORT`	`55000`	Manager API port
`MCP_HOST`	`0.0.0.0`	Server bind address
`MCP_PORT`	`3000`	Server port
`AUTH_MODE`	`bearer`	`oauth`, `bearer`, or `none`
`AUTH_SECRET_KEY`	auto-generated	JWT signing key
`AUTHLESS_ALLOW_WRITE`	`false`	Allow active response in authless mode
`ALLOWED_ORIGINS`	`https://claude.ai`	CORS origins (comma-separated)
`REDIS_URL`	—	Redis URL for multi-instance session storage

Wazuh Indexer (for alert search + vulnerabilities)

Variable	Default	Description
`WAZUH_INDEXER_HOST`	—	Indexer hostname
`WAZUH_INDEXER_PORT`	`9200`	Indexer port
`WAZUH_INDEXER_USER`	—	Indexer username
`WAZUH_INDEXER_PASS`	—	Indexer password

Full reference: Configuration Guide

API Endpoints

Endpoint	Method	Description
`/mcp`	POST/GET/DELETE	MCP Streamable HTTP (recommended)
`/sse`	GET	Legacy Server-Sent Events
`/health`	GET	Health check (no auth required)
`/metrics`	GET	Prometheus metrics
`/auth/token`	POST	Exchange API key for JWT
`/docs`	GET	OpenAPI documentation

Architecture

src/wazuh_mcp_server/
├── server.py           # MCP protocol + 48 tool handlers
├── config.py           # Environment-based configuration
├── auth.py             # JWT + API key authentication
├── oauth.py            # OAuth 2.0 with Dynamic Client Registration
├── security.py         # Rate limiting, CORS, input validation
├── monitoring.py       # Prometheus metrics, structured logging
├── resilience.py       # Circuit breakers, retries, graceful shutdown
├── session_store.py    # Pluggable sessions (in-memory + Redis)
└── api/
    ├── wazuh_client.py    # Wazuh Manager REST API client
    └── wazuh_indexer.py   # Wazuh Indexer (Elasticsearch) client

Take It Further: Autonomous Agentic SOC

Combine this MCP server with Wazuh OpenClaw Autopilot to build a fully autonomous Security Operations Center.

While this server gives you conversational access to Wazuh, OpenClaw deploys AI agents that work around the clock — triaging alerts, correlating incidents, and recommending responses without human intervention.

Manual SOC:    Alert → Analyst reviews → Hours → Response
Agentic SOC:   Alert → AI triages → Seconds → Response ready for approval

Explore OpenClaw Autopilot

Documentation

Guide	Description
Claude Integration	Claude Desktop setup and authentication
Configuration	Full configuration reference
Advanced Features	HA, serverless, compact mode
API Documentation	Per-tool documentation
Security	Security hardening guide
Troubleshooting	Common issues and solutions
Operations	Deployment, monitoring, maintenance

Contributing

We welcome contributions. See Issues for bugs and feature requests, Discussions for questions.

License

MIT

Acknowledgments

Wazuh — Open source security platform
Model Context Protocol — AI tool integration standard
Ollama — Local LLM inference
Open WebUI — Self-hosted AI chat interface
mcphost — MCP CLI host with LLM support

Contributors

Avatar	Username	Contributions
	@alokemajumder	Code, Issues, Discussions
	@gensecai-dev	Code, Discussions
	@aiunmukto	Code, PRs
	@Karibusan	Code, Issues, PRs
	@lwsinclair	Code, PRs
	@taylorwalton	PRs
	@MilkyWay88	PRs
	@kanylbullen	Code, PRs
	@Uberkarhu	Issues
	@cbassonbgroup	Issues
	@cybersentinel-06	Issues
	@daod-arshad	Issues
	@mamema	Issues
	@marcolinux46	Issues
	@matveevandrey	Issues
	@punkpeye	Issues
	@tonyliu9189	Issues
	@Vasanth120v	Discussions
	@gnix45	Discussions
	@melmasry1987	Discussions

Auto-updated by GitHub Actions

This server cannot be installed

license - permissive license

quality - not tested

maintenance

How are these scores calculated?

Maintenance

–Maintainers

14dResponse time

2wRelease cycle

19Releases (12mo)

Issues opened vs closed

Resources

GitHub Repository

Need Help?

Related Servers

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Appeared in Searches

Latest Blog Posts

Lightport: Open-Sourcing Glama's AI Gateway
By punkpeye on April 27, 2026.
open source
OpenAI
Tool Definition Quality Score (TDQS)
By punkpeye on April 3, 2026.
mcp
The Hackers Who Tracked My Sleep Cycle
By punkpeye on March 26, 2026.
security

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/gensecaihq/Wazuh-MCP-Server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server