Scurity

Sentinel is a robust, enterprise-grade Security MCP (Model Context Protocol) Server designed for reliability, compliance, and easy integration with IDEs like VS Code and Antigravity.

🛡️ Features

• Robust Execution: Automatic retries for Docker commands, graceful timeout handling, and custom error reporting.
• Compliance Ready: Built-in support for CIS Benchmark scanning via Trivy.
• Structured Logging: All logs are output in JSON format for easy parsing and monitoring.
• Dockerized Tools: Runs all security tools in isolated Docker containers—no local tool installation required.

🧰 Included Tools

Tool	Function	Docker Image
Semgrep	SAST (Static Analysis)	returntocorp/semgrep (Rules: OWASP Top 10, CWE Top 25, Security Audit)
Trivy	SCA & Compliance	aquasec/trivy
Grype	SCA (Vulnerability Scanning)	anchore/grype
Gitleaks	Secret Scanning	zricethezav/gitleaks
OWASP ZAP	DAST (Web Scanning)	owasp/zap2docker-stable
ClamAV	Malware Scanning	clamav/clamav
Schemathesis	API Fuzzing	schemathesis/schemathesis:stable
EOL Scanner	Runtime/Framework EOL Checks	Built-in (endoflife.date API)
Crypto Scanner	SSL/TLS Compliance	drwetter/testssl.sh
AI Threat Modeler	STRIDE Analysis	Built-in (LLM Powered + Code Context + Mermaid DFD)

🚀 Getting Started

Prerequisites

• Docker: Must be installed and running.
• Python: Version 3.13 or higher.

Installation

1. Clone the repository (if applicable) or navigate to the project directory:

   cd sentinel-mcp-server
   

2. Create a virtual environment:

   python3 -m venv .venv
   source .venv/bin/activate
   

3. Install dependencies:

   pip install .
   

Running the Server

To start the MCP server manually (for testing):

mcp run python src/sentinel/server.py

Manual Scanning (CLI)

You can also scan any project directory directly from the terminal using the included utility script:

# Scan a specific project directory
python3 scan_project.py /path/to/your/project

# Run only specific scans (e.g., secrets)
python3 scan_project.py /path/to/your/project --type secrets

💻 IDE Configuration

VS Code

To use Sentinel with the MCP Servers extension in VS Code, add the following to your MCP settings file (typically ~/Library/Application Support/Code/User/globalStorage/mcp-servers.json):

{
  "mcpServers": {
    "sentinel": {
      "command": "/Users/pranjalsharma/Documents/SourceCode/appsec/sentinel-mcp-server/.venv/bin/python3",
      "args": [
        "/Users/pranjalsharma/Documents/SourceCode/appsec/sentinel-mcp-server/src/sentinel/server.py"
      ],
      "env": {
        "SENTINEL_LOG_LEVEL": "INFO"
      }
    }
  }
}

Replace /ABSOLUTE/PATH/TO/... with the actual full path to your project directory.

⚙️ Configuration

You can configure Sentinel using environment variables:

Variable	Description	Default
SENTINEL_LOG_LEVEL	Logging level (DEBUG, INFO, WARN, ERROR)	INFO
SENTINEL_DOCKER_TIMEOUT	Timeout for Docker commands in seconds	600
SENTINEL_SEMGREP_IMAGE	Custom Docker image for Semgrep	returntocorp/semgrep
SENTINEL_TRIVY_IMAGE	Custom Docker image for Trivy	aquasec/trivy
SENTINEL_GRYPE_IMAGE	Custom Docker image for Grype	anchore/grype
SENTINEL_TESTSSL_IMAGE	Custom Docker image for testssl.sh	drwetter/testssl.sh
SENTINEL_SCHEMATHESIS_IMAGE	Custom Docker image for Schemathesis	schemathesis/schemathesis:stable
SENTINEL_LLM_API_KEY	API Key for AI Threat Modeling (e.g., OpenAI)	None (Falls back to heuristic)
SENTINEL_LLM_MODEL	LLM Model to use	gpt-4o

🏗️ Project Structure

src/sentinel/
├── core/           # Core logic (logging, exceptions, config)
├── services/       # Business logic (scanners, compliance)
├── tools/          # Tool execution (Docker runner)
└── server.py       # Main MCP entry point