mcp-server-wazuh

Wazuh MCP Server

A Rust-based server designed to bridge the gap between a Wazuh Security Information and Event Management (SIEM) system and applications requiring contextual security data, specifically tailored for the Claude Desktop Integration using the Model Context Protocol (MCP).

Overview

Modern AI assistants like Claude can benefit significantly from real-time context about the user's environment. For security operations, this means providing relevant security alerts and events. Wazuh is a popular open-source SIEM, but its API output isn't directly consumable by systems expecting MCP format.

Example Use Cases

The Wazuh MCP Server, by bridging Wazuh's security data with MCP-compatible applications, unlocks several powerful use cases:

• Delegated Alert Triage: Automate alert categorization and prioritization via AI, focusing analyst attention on critical events.
• Enhanced Alert Correlation: Enrich alerts by correlating with CVEs, OSINT, and other threat intelligence for deeper context and risk assessment.
• Dynamic Security Visualizations: Generate on-demand reports and visualizations of Wazuh data to answer specific security questions.
• Multilingual Security Operations: Query Wazuh data and receive insights in multiple languages for global team accessibility.
• Natural Language Data Interaction: Query Wazuh data using natural language for intuitive access to security information.
• Contextual Augmentation for Other Tools: Use Wazuh data as context to enrich other MCP-enabled tools and AI assistants.

Requirements

• An MCP (Model Context Protocol) compatible LLM client (e.g., Claude Desktop)
• A running Wazuh server (v4.x recommended) with the API enabled and accessible.
• Network connectivity between this server and the Wazuh API (if API interaction is used).

Installation

Option 1: Download Pre-built Binary (Recommended)

1. Download the Binary:
   • Go to the Releases page of the mcp-server-wazuh GitHub repository.
   • Download the appropriate binary for your operating system (e.g., mcp-server-wazuh-linux-amd64, mcp-server-wazuh-macos-amd64, mcp-server-wazuh-windows-amd64.exe).
   • Make the downloaded binary executable (e.g., chmod +x mcp-server-wazuh-linux-amd64).
   • (Optional) Rename it to something simpler like mcp-server-wazuh and move it to a directory in your system's PATH for easier access.

Option 2: Build from Source

1. Prerequisites:
   • Install Rust: https://www.rust-lang.org/tools/install
2. Build:
   git clone https://github.com/gbrigandi/mcp-server-wazuh.git cd mcp-server-wazuh cargo build --release
   The binary will be available at target/release/mcp-server-wazuh.

Configure Your LLM Client

The method for configuring your LLM client will vary depending on the client itself. For clients that support MCP (Model Context Protocol), you will typically need to point the client to the path of the mcp-server-wazuh executable.

Example for Claude Desktop:

Configure your claude_desktop_config.json file:

Replace /path/to/mcp-server-wazuh with the actual path to your binary and configure the environment variables as detailed in the Configuration section.

Once configured, your LLM client should be able to launch and communicate with the mcp-server-wazuh to access Wazuh security data.

Configuration

Configuration is managed through environment variables. A .env file can be placed in the project root for local development.

Note on VERIFY_SSL: For production environments using the Wazuh API, it is strongly recommended to set VERIFY_SSL=true and ensure proper certificate validation. Setting it to false disables certificate checks, which is insecure.

Architecture

The server is built using the rmcp framework and facilitates communication between MCP clients (e.g., Claude Desktop, IDE extensions) and the Wazuh MCP Server via stdio transport. The server interacts with the Wazuh Indexer API to fetch security alerts and other data.

Data Flow (stdio focus):

1. An application (e.g., an IDE extension, a CLI tool) launches the Wazuh MCP Server as a child process.
2. The application sends MCP-formatted requests (commands) to the server's stdin.
3. The Wazuh MCP Server reads the command from stdin.
4. Processing:
   • The server parses the MCP command.
   • If the command requires fetching data from Wazuh (e.g., "get latest alerts"):
     • The server connects to the Wazuh API (authenticating if necessary using configured credentials like WAZUH_USER, WAZUH_PASS).
     • It fetches the required data (e.g., security alerts).
     • The server's transformation logic (src/mcp/transform.rs) processes each alert, mapping Wazuh fields to MCP fields.
   • If the command is internal (e.g., a status check specific to the MCP server), it processes it directly.
5. The server sends an MCP-formatted JSON response (e.g., transformed alerts, command acknowledgment, or error messages) to the application via its stdout.
6. The application reads and processes the MCP response from the server's stdout.

This stdio interaction allows for tight integration with local development tools or other applications that can manage child processes. An optional HTTP endpoint (/mcp) may also be available for clients that prefer polling.

Building

Prerequisites

• Install Rust: https://www.rust-lang.org/tools/install
• Install Docker and Docker Compose (optional, for containerized deployment): https://docs.docker.com/get-docker/

Local Development

1. Clone the repository:
   git clone https://github.com/gbrigandi/mcp-server-wazuh.git cd mcp-server-wazuh
2. Configure (if using Wazuh API):
   • Copy the example environment file: cp .env.example .env
   • Edit the .env file with your specific Wazuh API details (WAZUH_HOST, WAZUH_PORT, WAZUH_USER, WAZUH_PASS).
3. Build:
   cargo build
4. Run:
   cargo run # Or use the run script (which might set up stdio mode): # ./run.sh
   If the HTTP server is enabled, it will start listening on the port specified by MCP_SERVER_PORT (default 8000). Otherwise, it will operate in stdio mode.

Stdio Mode Operation

The server communicates via stdin and stdout using JSON-RPC 2.0 messages, adhering to the Model Context Protocol (MCP).

Example interaction flow:

1. Client Application (e.g., IDE extension) starts the mcp-server-wazuh process.
2. Client sends initialize request to server's stdin:
   { "jsonrpc": "2.0", "id": 0, "method": "initialize", "params": { "protocolVersion": "2024-11-05", "capabilities": { "sampling": {}, "roots": { "listChanged": true } }, "clientInfo": { "name": "mcp-inspector", "version": "0.11.0" } } }
3. Server sends initialize response to client via stdout:
   { "jsonrpc": "2.0", "id": 1, "result": { "protocolVersion": "2024-11-05", "capabilities": { "prompts": {}, "resources": {}, "tools": {} }, "serverInfo": { "name": "rmcp", "version": "0.1.5" }, "instructions": "This server provides tools to interact with a Wazuh SIEM instance for security monitoring and analysis.\nAvailable tools:\n- 'get_wazuh_alert_summary': Retrieves a summary of Wazuh security alerts. Optionally takes 'limit' parameter to control the number of alerts returned (defaults to 100)." } }
4. Client sends notifications/initialized to server's stdin: (This is a notification, so id is omitted by the client.)
   { "jsonrpc": "2.0", "method": "notifications/initialized" }
5. Client requests available tools by sending tools/list to server's stdin:
   { "jsonrpc": "2.0", "id": 1, "method": "tools/list", "params": {} }
6. Server responds with the list of tools to client via stdout:
   { "jsonrpc": "2.0", "id": 2, "result": { "tools": [ { "name": "get_wazuh_alert_summary", "description": "Retrieves a summary of Wazuh security alerts. Returns formatted alert information including ID, timestamp, and description.", "inputSchema": { "$schema": "http://json-schema.org/draft-07/schema#", "properties": { "limit": { "description": "Maximum number of alerts to retrieve (default: 100)", "format": "uint32", "minimum": 0.0, "type": ["integer", "null"] } }, "title": "GetAlertSummaryParams", "type": "object" } } ] } }
7. Client calls the get_wazuh_alert_summary tool by sending tools/call to server's stdin:
   { "jsonrpc": "2.0", "id": 3, "method": "tools/call", "params": { "name": "get_wazuh_alert_summary", "arguments": { "limit": 5 } } }
8. Server receives on stdin, processes the get_wazuh_alert_summary call (which involves querying the Wazuh Indexer API and transforming the data).
9. Server sends tools/call response with formatted alerts to client via stdout:
   { "jsonrpc": "2.0", "id": 3, "result": { "content": [ { "type": "text", "text": "Alert ID: 1747091815.1212763\nTime: 2024-01-15T10:30:45.123Z\nAgent: web-server-01\nLevel: 7\nDescription: Attached USB Storage" }, { "type": "text", "text": "Alert ID: 1747066333.1207112\nTime: 2024-01-15T10:25:12.456Z\nAgent: database-server\nLevel: 5\nDescription: New dpkg (Debian Package) installed." } ], "isError": false } }
   Or, if no alerts are found:
   { "jsonrpc": "2.0", "id": 3, "result": { "content": [ { "type": "text", "text": "No Wazuh alerts found." } ], "isError": false } }
   Or, if there's an error connecting to Wazuh:
   { "jsonrpc": "2.0", "id": 3, "result": { "content": [ { "type": "text", "text": "Error retrieving alerts from Wazuh: HTTP request error: connection refused" } ], "isError": true } }

Development & Testing

• Code Style: Uses standard Rust formatting (cargo fmt).
• Linting: Uses Clippy (cargo clippy).
• Testing: Contains unit tests for transformation logic and integration tests. For stdio, tests might involve piping input/output to a test harness. For HTTP, tests use a mock Wazuh API server (httpmock) and a test MCP client.
  # Run all tests cargo test # Run specific integration test (example for HTTP tests) # cargo test --test integration_test # Run tests with detailed logging RUST_LOG=debug cargo test
• See tests/README.md for more details on running tests and using the test client CLI.

License

This project is licensed under the MIT License.