Dot Ai
vfarcic/dot-ai · 324 stars · TypeScript · MIT
MCP server Intelligent dual-mode agent for deploying applications to ANY Kubernetes cluster through dynamic discovery and plain English governance
Install
The repo has no one-line install. Follow its README.
Files
DevOps AI Toolkit
AI-powered platform engineering and DevOps automation through intelligent Kubernetes operations and conversational workflows.
AI Engine Docs | MCP Setup
Overview
DevOps AI Toolkit brings AI-powered intelligence to platform engineering, Kubernetes operations, and development workflows. Access it through MCP for AI coding assistants or the CLI for direct agent integration.
Key capabilities:
- Natural language cluster querying and exploration
- Intelligent Kubernetes deployment recommendations
- AI-powered issue remediation and root cause analysis
- Organizational pattern and policy management
- Semantic search over organizational documentation
- Automated repository setup with governance files
- Shared prompt libraries for consistent workflows
- Untrusted-content boundary separating cluster output from operator instruction in remediation and Day 2 operations
Deployment
For the easiest setup, we recommend installing the complete dot-ai stack which includes all components pre-configured. See the Stack Installation Guide.
For individual component installation, see the Deployment Guide.
Support
- 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
Contributing & Governance
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
License
MIT License - see LICENSE file for details.
Telemetry
This project collects anonymous usage analytics to improve the product. Learn more or opt out.
Acknowledgments
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.
Facts
- Kind
- MCP server
- Repo
- vfarcic/dot-ai
- Group
- Uncategorized
- Stars
- 324
- License
- MIT
- Language
- TypeScript
- Last push
- 2026-10-08
- Forks
- 73
- 1Everythingmodelcontextprotocol/serversThis MCP server attempts to exercise all the features of the MCP protocol. It is not intended to be a useful server, but rather a test server for builders of MCP clients. It implements prompts, tools, resources, sampling, and more to showcase MCP capabilities.85.8k
- 2Fetchmodelcontextprotocol/serversA Model Context Protocol server that provides web content fetching capabilities. This server enables LLMs to retrieve and process content from web pages, converting HTML to markdown for easier consumption.85.8k
- 3Gitmodelcontextprotocol/serversA Model Context Protocol server for Git repository interaction and automation. This server provides tools to read, search, and manipulate Git repositories via Large Language Models.85.8k
- 4Memorymodelcontextprotocol/serversA basic implementation of persistent memory using a local knowledge graph. This lets Claude remember information about the user across chats.85.8k
- 5Sequential Thinkingmodelcontextprotocol/serversAn MCP server implementation that provides a tool for dynamic and reflective problem-solving through a structured thinking process.85.8k
- 6Timemodelcontextprotocol/serversA Model Context Protocol server that provides time and timezone conversion capabilities. This server enables LLMs to get current time information and perform timezone conversions using IANA timezone names, with automatic system timezone detection.85.8k
