keides2/coverity-connect-mcp

Coverity Connect MCP Server

English |

A Model Context Protocol (MCP) server that provides seamless integration between AI assistants (like Claude Desktop) and Black Duck Coverity Connect static analysis platform.

Transform your Coverity workflow with natural language commands and automated analysis through AI-powered interactions.

🚀 Features

🔍 Comprehensive Coverity Integration

• Project Management: List and explore Coverity projects and streams
• Snapshot Analysis: Detailed defect analysis with automated reporting
• Security Focus: Specialized security vulnerability detection and analysis
• CI/CD Automation: Automated pipeline integration for continuous quality monitoring
• Quality Reports: Executive-level quality dashboards and trend analysis

🤖 AI-Powered Analysis

• Natural Language Queries: "Show me critical security issues in project X"
• Intelligent Filtering: Automatic prioritization of high-impact defects
• Contextual Recommendations: AI-driven remediation suggestions
• Trend Analysis: Historical data analysis and quality metrics

🛠️ Enterprise Ready

• SOAP API Integration: Full Coverity Connect Web Services support
• Authentication: Secure auth-key based authentication
• Proxy Support: Corporate network and proxy configuration
• Multi-Platform: Windows, macOS, and Linux support
• Docker Ready: Containerized deployment for enterprise environments

📦 Installation

⚠️ Note: This package is not yet published to PyPI or Docker Hub. Please use the source installation method until official packages are released.

Current Installation Method (Recommended)

# Clone the repository
git clone https://github.com/keides2/coverity-connect-mcp.git
cd coverity-connect-mcp

# Install in development mode
pip install -e .

Alternative: Direct Installation from GitHub

# Install directly from GitHub
pip install git+https://github.com/keides2/coverity-connect-mcp.git

Future Installation Methods

Once the package is published, these installation methods will be available:

PyPI Installation (Coming Soon)

pip install coverity-connect-mcp

Docker Installation (Coming Soon)

docker pull keides2/coverity-connect-mcp:latest

Development Installation

For development purposes:

git clone https://github.com/keides2/coverity-connect-mcp.git
cd coverity-connect-mcp

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install with development dependencies
pip install -e ".[dev]"

⚙️ Configuration

1. Environment Variables

Create a .env file or set environment variables:

# Required - Coverity Connect Authentication
export COVAUTHUSER="your_coverity_username"
export COVAUTHKEY="your_coverity_auth_key"

# Required - Coverity Server
export COVERITY_HOST="your-coverity-server.com"
export COVERITY_PORT="443"
export COVERITY_SSL="True"

# Optional - Local Workspace
export COVERITY_BASE_DIR="/path/to/coverity/workspace"

# Optional - Corporate Proxy (if needed)
export PROXY_HOST="your-proxy-server.com"
export PROXY_PORT="3128"
export PROXY_USER="proxy_username"  # if authentication required
export PROXY_PASS="proxy_password"  # if authentication required

2. Claude Desktop Integration

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "coverity-connect": {
      "command": "coverity-mcp-server",
      "env": {
        "COVAUTHUSER": "${COVAUTHUSER}",
        "COVAUTHKEY": "${COVAUTHKEY}",
        "COVERITY_HOST": "your-coverity-server.com"
      }
    }
  }
}

3. Docker Configuration

Note: Since the Docker image is not yet published, you can build it locally:

# docker-compose.yml
version: '3.8'
services:
  coverity-mcp:
    build: .  # Build from local source
    # Future: image: keides2/coverity-connect-mcp:latest
    environment:
      - COVAUTHUSER=${COVAUTHUSER}
      - COVAUTHKEY=${COVAUTHKEY}
      - COVERITY_HOST=${COVERITY_HOST}
      # Optional proxy settings
      - PROXY_HOST=${PROXY_HOST}
      - PROXY_PORT=${PROXY_PORT}
    ports:
      - "8000:8000"

🎯 Usage Examples

Basic Project Analysis

Show me all Coverity projects and their current status

Security-Focused Analysis

Analyze the latest snapshot of project "MyWebApp" and focus on high-severity security vulnerabilities. Provide specific remediation recommendations.

Quality Reporting

Generate a comprehensive quality report for project "MyProject" including trends over the last 30 days

CI/CD Integration

Run automated Coverity analysis for group "web-team", project "frontend", branch "main" with commit message "Security fixes"

Advanced Filtering

Show me all CERT-C violations in project "EmbeddedSystem" with impact level "High" and provide code examples for fixes

🛠️ Available Tools

📚 Documentation

English

• - Detailed setup instructions for all platforms
• - Complete configuration options and security settings
• - Comprehensive API documentation with examples
• - Complete development to production setup
• - Environment-specific configurations and examples

日本語 (Japanese)

• - 詳細なセットアップ手順（全プラットフォーム対応）
• - 完全な設定オプションとセキュリティ設定
• - 包括的なAPI仕様書と使用例
• - 開発から本番環境までの完全セットアップ
• - 環境別設定とサンプル

🌐 多言語サポート: 英語と日本語の完全ドキュメントを提供しています。すべてのガイドにはステップバイステップの手順、トラブルシューティングのヒント、実用的な例が含まれています。

🧪 Testing

# Run unit tests
pytest tests/

# Run integration tests
pytest tests/ -m integration

# Run with coverage
pytest --cov=coverity_mcp_server tests/

# Test with Docker
docker-compose -f docker-compose.test.yml up --abort-on-container-exit

🤝 Contributing

We welcome contributions! Please see our for details.

Development Setup

git clone https://github.com/keides2/coverity-connect-mcp.git
cd coverity-connect-mcp
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
pip install -e ".[dev]"
pre-commit install

Submitting Changes

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

📄 License

This project is licensed under the MIT License - see the file for details.

🙏 Acknowledgments

• Black Duck Coverity for providing the static analysis platform
• Anthropic for the Model Context Protocol and Claude AI
• Open Source Community for the foundational libraries and tools

📞 Support

• GitHub Issues: Report bugs or request features
• Discussions: Community support and questions
• Security Issues: Please see our

🗺️ Roadmap

• v1.1: Advanced filtering and custom views
• v1.2: Multi-tenant support and user management
• v1.3: REST API alongside SOAP support
• v1.4: Machine learning-powered defect prioritization
• v2.0: Plugin architecture and third-party integrations

Made with ❤️ for the software security community

Transform your static analysis workflow with the power of AI