Dot Ai

io.github.vfarcicPublished by GitHub account vfarcicv0.112.0Updated Oct 25, 2026

AI-powered development platform for Kubernetes deployments and intelligent automation

VerifiedSTDIODesktop onlyCloud & Infrastructure Knowledge & Memory

Server details

Identifier: io.github.vfarcic/dot-ai
Transport: STDIO
Runtime: Desktop only
Trust: Verified
Published: Sep 16, 2026

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Overview

AI-generated overview

A local MCP server that gives AI assistants Kubernetes operations help: natural-language cluster queries, deployment recommendations and issue remediation.

What you can do: Query and explore Kubernetes clusters in natural language, including deployment recommendations for workloads and AI-assisted issue remediation with root cause analysis, with cluster output kept separate from operator instruction as untrusted content. Manage organizational patterns and policies, and run semantic search over organizational documentation. Set up repositories with governance files and share prompt libraries for consistent workflows. The manifest lists no individual tools, so exact tool names are not documented here.
When to use it: Useful for platform engineering and DevOps teams that want an assistant to inspect Kubernetes clusters, get deployment guidance, troubleshoot issues, or look up internal documentation and policies during day-to-day operations.
Requirements: Runs as a local process over stdio, installed from the npm package @vfarcic/dot-ai, so Node.js is needed. The README recommends installing the complete dot-ai stack for easiest setup, with individual component installation covered in its deployment guide. No environment variables, headers or authentication are declared in the manifest.

Before you install

The README states the project collects anonymous usage analytics, with an option to opt out. It also describes an untrusted-content boundary between cluster output and operator instruction, which matters when acting on cluster data. The manifest declares no credentials, but cluster access and any write actions are not detailed here, so review the deployment guide before use.

Installation

In SourceWeft

Open Dot Ai in the dashboard and add it to a workspace.
Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

DevOps AI Toolkit

[DevOps AI Toolkit Logo]

[npm version] [npm downloads] [GitHub release] [License] [Project Status] [OpenSSF Scorecard] [GitHub stars]

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.

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.

Source: README.md at commit a1118c5

Tools

SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

v0.112.0LatestSep 16, 2026

Score

50% of the applicable checks met

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Reached in the last 30 days25 pts
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Auth declared10 pts
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Tools listed15 pts
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DescriptionRequired15 pts
Logo10 pts
Documentation15 pts
License10 pts