How do I install Dot Ai?

Dot Ai is a local plugin. Install it using npm package: @vfarcic/dot-ai and add the generated configuration snippet to your AI app's MCP config file. Then restart your AI app.

What AI apps work with Dot Ai?

Dot Ai uses the Model Context Protocol (MCP) and works with any MCP-compatible AI app, including Claude, ChatGPT / Codex, Gemini, Copilot, Cursor, and more.

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Dot Ai MCP Server

by Vfarcic

Developer ToolsLow Risk10.0MCP RegistryLocal

Free

Server data from the Official MCP Registry

AI-powered development platform for Kubernetes deployments and intelligent automation

About

AI-powered development platform for Kubernetes deployments and intelligent automation

Security Report

10.0

Low Risk10.0Low Risk

Valid MCP server (2 strong, 2 medium validity signals). No known CVEs in dependencies. Package registry verified. Imported from the Official MCP Registry.

8 files analyzed · 1 issue found

Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.

Permissions Required

This plugin requests these system permissions. Most are normal for its category.

file_system

Check that this permission is expected for this type of plugin.

env_vars

Check that this permission is expected for this type of plugin.

How to Install

Add this to your MCP configuration file:

{
  "mcpServers": {
    "io-github-vfarcic-dot-ai": {
      "args": [
        "-y",
        "@vfarcic/dot-ai-mock-server"
      ],
      "command": "npx"
    }
  }
}

Documentation

View on GitHub

From the project's GitHub README.

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

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.

AI Engine Docs | MCP Setup

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.

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Dot Ai MCP Server

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