MCP Server
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Optimizing Security with Wazuh MCP Server: Powerful Integration with SIEM

The Wazuh MCP Server is a specialized solution designed to integrate Wazuh SIEM systems with applications relying on the Model Context Protocol (MCP). This innovative server enables seamless interaction with Wazuh security alerts by transforming API data into MCP-compatible formats, unlocking advanced capabilities like AI-driven alert analysis and natural language interaction with security data.

17
GitHub Stars
5-10 minutes
Setup Time
1
Target Groups
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Server Details

Language
Rust
Status
maintained
Version
1.0
Updated6/13/2025
Dependencies
0

Compatibility

claude desktop
cursor
vscode
windsurf

What's Inside

Navigate through comprehensive documentation and guides

Overview

Level 1

Quick Start

Level 1

Features

Level 1

Installation

Level 1

Configuration

Level 2

Usage Examples

Level 1

Tools & Commands

Level 1

Troubleshooting

Level 1

FAQ

Level 1

Community & Support

Level 1

Get Started in 3 Steps

Get up and running in just 5 minutes

Step-by-step guide with copy-paste commands
1

Install Prerequisites

2 minutes

Install Node.js and Ollama on your system

npm install -g ollama
2

Setup MCP Server

2 minutes

Clone repository and install dependencies

git clone https://github.com/gbrigandi/mcp-server-wazuh && npm install
3

Connect to Claude

1 minute

Add server to Claude Desktop configuration

Edit claude_desktop_config.json

Powerful Features

Discover what makes this MCP server exceptional and how it can transform your workflow

Transforms Wazuh security alerts into MCP-compatible JSON.

Supports AI-driven categorization and enrichment of security alerts.

Provides dynamic visualization tools for security reporting.

Enables natural language queries of Wazuh security data.

Supports optional HTTP endpoints for broader network integrations.

Utilizes JSON-RPC 2.0 for high-efficiency communication between systems.

Offers configurable SSL handling and authentication settings.

Technical Capabilities

get_wazuh_alert_summary: Retrieves a summary of Wazuh security alerts, returning formatted alert information such as ID, timestamp, and description. Accepts an optional 'limit' parameter to control the number of alerts retrieved (default is 100).

About This Server

The Wazuh MCP Server serves as a critical bridge between Wazuh SIEM systems and MCP-enabled tools, empowering security teams by automating alert categorization, enriching security data with threat intelligence, and enabling intuitive natural language querying. Through its Rust-based architecture and support for JSON-RPC 2.0 protocols, the server provides high-performance, flexible deployment options, ensuring easy integration with AI tools and real-time access to Wazuh alert data for enhanced decision-making. Whether deployed as a binary or built from source, the server provides comprehensive features tailored to meet the demands of modern security operations.

Tools & Capabilities

Explore the powerful tools this server provides

Available Tools

get_wazuh_alert_summary

Retrieves a summary of Wazuh security alerts, returning formatted alert information such as ID, timestamp, and description. Accepts an optional 'limit' parameter to control the number of alerts retrieved (default is 100).

visualize_security_reports

Generates dynamic security visualizations from Wazuh alert data for threat review and analysis. Supports report formats like graphs, timelines, and detailed mappings.

categorize_alerts

Automatically classifies and prioritizes security alerts based on severity, category, or threat level using AI-driven logic.

Installation & Setup

Complete guide to get this MCP server running in your environment

Before You Start

There are two ways to add an MCP server to Cursor and Claude Desktop App:

  1. Globally: Available in all of your projects by adding it to the global MCP settings file.
  2. Per Project: Available only within a specific project by adding it to the project's MCP settings file.

Cursor IDE

Adding an MCP Server to Cursor Globally

  1. Go to **Cursor Settings > MCP** and click **Add new global MCP server**.
  2. This will open the `~/.cursor/mcp.json` file.
  3. Add your MCP server configuration like the following:
Configuration Example
{
  "mcpServers": {
    "cursor-rules-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "cursor-rules-mcp"
      ]
    }
  }
}

Claude Desktop

Adding an MCP Server to Claude Desktop App Globally

  1. Go to **Claude Settings > MCP Servers** and click **Add Global MCP Server**.
  2. This will open the `~/.claude/mcp.json` file (or you can navigate there manually).
  3. Add your MCP server configuration like the following:
Configuration Example
{
  "mcpServers": {
    "cursor-rules-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "cursor-rules-mcp"
      ]
    }
  }
}

Step-by-Step Setup

Detailed instructions to get everything running

2

Either download the pre-built binary for your operating system or build the server from source using Rust:

  • Install Rust (https://rust-lang.org/tools/install).
  • Clone the repo using git clone https://github.com/gbrigandi/mcp-server-wazuh.git.
  • Navigate to the folder: cd mcp-server-wazuh and run cargo build --release.
3

Configure the .env file with Wazuh API settings (e.g., WAZUH_HOST, WAZUH_USER, WAZUH_PASS).

4

Start the server with the binary or via cargo run. Leverage JSON-RPC tools for integration or optional HTTP endpoints for broader connectivity.

Use Cases

Real-world applications and scenarios where this server excels

Streamlining security alert triaging with AI-driven prioritization to reduce manual workload.

Generating multilingual, context-driven reports for global security teams.

Enriching alert data with correlated intelligence from OSINT and CVE databases for deeper threat understanding.

Customizing AI assistants like Claude Desktop to query, process, and present Wazuh security data in natural language.

Providing real-time threat visualizations for management and auditing use.

Success Stories

See how others have successfully implemented this MCP server

Real-world Application: Streamlining Security Alert Triaging With Ai Driven Prioritization To Reduce Manual Workload.

Scenario

An organization implemented Optimizing Security with Wazuh MCP Server: Powerful Integration with SIEM to address their specific need for streamlining security alert triaging with ai-driven prioritization to reduce manual workload.

Implementation

They configured the MCP server with specialized AI models tailored to their streamlining security alert triaging with ai-driven prioritization to reduce manual workload. requirements, enabling comprehensive analysis and decision support

Outcome

Achieved significant improvements in streamlining security alert triaging with ai-driven prioritization to reduce manual workload. efficiency and quality through multi-perspective AI analysis

Real-world Application: Generating Multilingual, Context Driven Reports For Global Security Teams.

Scenario

An organization implemented Optimizing Security with Wazuh MCP Server: Powerful Integration with SIEM to address their specific need for generating multilingual, context-driven reports for global security teams.

Implementation

They configured the MCP server with specialized AI models tailored to their generating multilingual, context-driven reports for global security teams. requirements, enabling comprehensive analysis and decision support

Outcome

Achieved significant improvements in generating multilingual, context-driven reports for global security teams. efficiency and quality through multi-perspective AI analysis

Real-world Application: Enriching Alert Data With Correlated Intelligence From Osint And Cve Databases For Deeper Threat Understanding.

Scenario

An organization implemented Optimizing Security with Wazuh MCP Server: Powerful Integration with SIEM to address their specific need for enriching alert data with correlated intelligence from osint and cve databases for deeper threat understanding.

Implementation

They configured the MCP server with specialized AI models tailored to their enriching alert data with correlated intelligence from osint and cve databases for deeper threat understanding. requirements, enabling comprehensive analysis and decision support

Outcome

Achieved significant improvements in enriching alert data with correlated intelligence from osint and cve databases for deeper threat understanding. efficiency and quality through multi-perspective AI analysis

Frequently Asked Questions

Get answers to common questions and troubleshooting tips

Common Questions

Everything you need to know to get started

Related Topics & Technologies

Explore related concepts and technologies

Technologies

large language models
LLMs
generative AI
AI personas
machine learning models
natural language processing
model context protocol
API integration

Categories

rust
api-integration

Ready to Transform Your Workflow?

Join thousands of developers who are already using this MCP server to enhance their productivity

17
GitHub Stars
5-10 minutes
Setup Time
complex
Complexity

Free & Open Source • No vendor lock-in • Active community support