mcp-server

devops-ai-guidelines: Accelerate AI‑driven DevOps mastery

Name: devops-ai-guidelines: Accelerate AI‑driven DevOps mastery
Author: VersusControl

Boost your team’s AI DevOps skills with curated learning paths, actionable tips, and enterprise‑grade guidelines. Ideal for founders scaling cloud operations. 1.5k+ GitHub stars.

1,545 stars+19★ this week390 forksPythonGuide quality 8/10 · reviewed Oct 4Updated 9/24/2026100% free · open source

What it does

Devops-ai-guidelines provides comprehensive DevOps guidelines and learning paths for founders to improve their development and operations practices

When to use it

•When setting up a new DevOps pipeline and needing guidance on best practices
•When trying to improve existing development and operations workflows
•When looking for practical tips and enterprise guidelines for DevOps implementation

Ready-to-paste prompt

Explore the 'getting-started' section in the README.md file to get started with devops-ai-guidelines

Heads up: The project is hosted on GitHub, so a GitHub account and git version control system are required to clone and use the repository

Saves to your device

Use with Claude

New

Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.

🛠️ Technical setup

Expect 20–40 minutes in a terminal — or let your AI agent drive it.

Try it instantly — no install

Claude Code

mkdir -p ~/.claude/skills/devops-ai-guidelines && curl -fsSL https://workflowstacks.com/api/skills/devops-ai-guidelines/claude-skill -o ~/.claude/skills/devops-ai-guidelines/SKILL.md

Open in another AI app

Opens the app with this repo with the prompt ready to go — no copy-paste needed.

Connect the whole catalog (MCP)

claude mcp add --transport http workflowstacks https://workflowstacks.com/api/mcp

Adds a WorkflowStacks connector to Claude Code: search and load any skill here by chatting.

How devops-ai-guidelines: Accelerate AI‑driven DevOps mastery works

Codeflow

Free to inspect

Devops-ai-guidelines: Accelerate AI‑driven DevOps mastery is a large Python project (~18k lines across 247 code files, plus 9 test files). It is a full software project: use it through its install path rather than reading it end to end. Last commit a month ago, MIT license, has a test suite.

Size

Large codebase

~18k lines · 247 code files · ~3 h to skim

Setup

Developer setup

A real software project. Use it via its install path; don't expect to read it all.

Runs on

Python

No API keys detected

Python 64%Go 33%Makefile 1%Shell 1%

Where to start reading

1
README.md
Start here — what it does and how to install it

What's in each folder

03-ai-agent-for-devops/Folder224 files

02-mcp-for-devops/Folder127 files

07-evaluating-ai-agents/Folder98 files

resources/Folder17 files

04-ai-agent-for-monitoring/Folder15 files

05-ai-project-management/Folder12 files

06-sre-agent-brain/Folder12 files

01-ai-roadmap-for-devops/Folder6 files

READMEHas testsDocumentedNo CIMIT licenseUpdated this month