AI-powered platform engineering and DevOps automation through intelligent Kubernetes operations and conversational workflows.
DevOps AI Toolkit brings AI-powered intelligence to platform engineering, Kubernetes operations, and development workflows. Built on the Model Context Protocol (MCP), it integrates seamlessly with Claude Code, Cursor, and VS Code.
Key capabilities:
- Intelligent Kubernetes deployment recommendations
- AI-powered issue remediation and root cause analysis
- Organizational pattern and policy management
- Automated repository setup with governance files
- Shared prompt libraries for consistent workflows
- Kubernetes Setup - Recommended: Full features with autonomous capability scanning
- ToolHive Setup - Operator-managed Kubernetes deployment
- Docker Setup - Local development (manual capability scanning only)
- NPX Setup - Quick trials with Node.js
- Support Guide - How to get help and where to ask questions
- GitHub Issues: Bug reports and feature requests
- GitHub Discussions: Community Q&A and discussions
We welcome contributions from the community! Please review:
- Contributing Guidelines - How to contribute code, docs, and ideas
- Code of Conduct - Community standards and expectations
- Security Policy - How to report security vulnerabilities
- Governance - Project governance and decision-making
- Maintainers - Current project maintainers
- Roadmap - Project direction and priorities
Your feedback shapes dot-ai's future! After using the tools, you may occasionally see a feedback prompt - we'd love to hear what's working and what could be better.
MIT License - see LICENSE file for details.
DevOps AI Toolkit is built on:
- Model Context Protocol for AI integration framework
- Vercel AI SDK for unified AI provider interface
- Kubernetes for the cloud native foundation
- CNCF for the cloud native ecosystem
DevOps AI Toolkit - Making cloud native operations accessible through AI-powered intelligence.