Agentic DevOps

The concept of Agentic DevOps got introduced in Microsoft Build conference 2025. Agentic DevOps is a paradigm, not a product. It's accessible to all, regardless of your tech stack or tooling. Use AI-powered tools like Cursor, Windsurf, Claude Code, Continue, Cline, or open-source models like Llama 4, Mistral, DeepSeek, Qwen. Deploy on-prem with vLLM, SGLang, or in the cloud with AWS, GCP, Azure.

Agentic DevOps with DSPy + MCP

A comprehensive demonstration of Agentic DevOps using DSPy and Model Context Protocol (MCP). The convep

This suite includes three specialized agents and a combined demo showcasing automated PR reviews, tech debt analysis, and incident response.

🎯 Features

• PR Review Agent: Automated security analysis, documentation review, and impact assessment
• Tech Debt Agent: Dependency analysis, code complexity scanning, and test coverage reporting
• Incident Response Agent: Automated incident diagnosis, remediation, and reporting

📋 Prerequisites

• Python 3.8+
• Node.js 14+
• OpenAI API key
• GitHub personal access token
• Mac OS X or Linux (Windows support may vary)

🚀 Installation

1. Create and activate a virtual environment:

python3 -m venv venv
source venv/bin/activate  # On Windows: .\venv\Scripts\activate

2. Clone the repository:

git clone https://github.com/superagenticai/agentic-devops.git
cd agentic-devops

3. Install Python dependencies:

pip install "agenspy[mcp]" dspy openai

4. Install Node.js dependencies:

npm install -g @modelcontextprotocol/server-github

⚙️ Configuration

1. Set up environment variables:

# For macOS/Linux
export OPENAI_API_KEY="your-openai-key"
export GITHUB_TOKEN="your-github-token"

# For Windows PowerShell
$env:OPENAI_API_KEY="your-openai-key"
$env:GITHUB_TOKEN="your-github-token"

Alternatively, create a .env file:

OPENAI_API_KEY=your-openai-key
GITHUB_TOKEN=your-github-token

🖥️ Running Individual Demos

PR Review Agent

python pr_review_agent.py

This will analyze a sample PR and provide:

• Security analysis
• Documentation review
• Implementation suggestions
• Impact assessment

Tech Debt Agent

python tech_debt_agent.py

This will scan a repository for:

• Deprecated dependencies
• Complex code modules
• Test coverage gaps
• Refactoring opportunities

Incident Response Agent

python incident_response_agent.py

This will simulate incident handling with:

• Automated diagnostics
• Remediation attempts
• Incident reporting
• On-call notifications

🎮 Running the Complete Demo

python agentic_devops_demo.py

This will run all three agents in sequence, demonstrating:

1. PR review workflow
2. Technical debt analysis
3. Incident response simulation

📁 Project Structure

agentic-devops/
├── pr_review_agent.py      # PR review automation
├── tech_debt_agent.py      # Technical debt analysis
├── incident_response_agent.py  # Incident response automation
└── README.md

🔑 API Keys and Permissions

OpenAI API Key

1. Visit OpenAI API
2. Create an account or log in
3. Navigate to API Keys section
4. Create a new secret key
5. Copy and set as OPENAI_API_KEY

GitHub Token

1. Visit GitHub Settings > Developer Settings
2. Generate new token (classic)
3. Select scopes:
   • repo (full access)
   • read:org
   • workflow
4. Copy and set as GITHUB_TOKEN

🤝 Contributing

1. Fork the repository
2. Create your feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request

⚠️ Common Issues

1. MCP Server Connection Failed

   # Check if server is running
   ps aux | grep mcp
   # Restart server
   npx @modelcontextprotocol/server-github

2. API Key Issues

   # Verify environment variables
   echo $OPENAI_API_KEY
   echo $GITHUB_TOKEN

3. Dependencies Missing

   # Reinstall dependencies
   pip install -r requirements.txt
   npm install -g @modelcontextprotocol/server-github

📝 License

MIT License - feel free to use and modify for your needs.

🙋‍♂️ Support

For issues and questions:

1. Check the Issues section
2. Create a new issue with detailed information