
Devops Practices
io.github.ai-4-devopsPublished by GitHub account ai-4-devopsv1.4.0Updated Nov 10, 2026
Productivity framework for DevOps engineers using AI assistance (Claude Code) while working on PoCs
Overview
Local MCP server that gives an AI assistant reusable DevOps practice documents and project file templates (tracker, runbook, docs) for PoC work.
- What you can do
- List and read the bundled DevOps practice documents, organized by workflow, version control, infrastructure and documentation groups
- List and fetch file templates such as TRACKER, CURRENT-STATE, CLAUDE, RUNBOOK and issue-tracking files
- Render a template with variable substitution, filling placeholders like date, timestamp, user and custom project values
- Serve as a shared, centralized source of practices so projects do not need large per-project instruction files
- When to use it
- Useful for DevOps engineers running proof-of-concept or infrastructure projects with an AI coding assistant who want consistent tracking, documentation, runbook and git conventions without repeating long instruction files in every project.
- Requirements
- Runs locally as a Python process (PyPI package devops-practices-mcp, started with python3 or uvx); the README also describes cloning the repository and installing its requirements. No accounts, API keys or environment variables are declared; the README's example config sets PYTHONUNBUFFERED.
Installation
In SourceWeft
- Open Devops Practices 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 Practices - MCP Server
[CI/CD Pipeline] [License: MIT] [Version] [MCP Registry] [PyPI]
mcp-name: io.github.ai-4-devops/devops-practices
Purpose: Productivity framework for DevOps engineers using AI assistance (Claude Code) while working on PoCs.
Type: Model Context Protocol (MCP) Server for Claude Code
Version: 1.4.0
Status: 🎉 Officially Published in the MCP Registry (Published: February 18, 2026)
Published Versions:
- 📦 PyPI: v1.4.0 → Git tag v1.4.0 (
34ca572) - 🌐 MCP Registry: v1.4.0 → Git tag v1.4.0 (
34ca572) - 🚀 Latest Development: main branch (may include unreleased features)
Who is this for? DevOps engineers using Claude Code (VS Code plugin) for PoC development. What it does: Provides structure (TRACKER, ISSUES, docs, SoPs) so you can focus on building without worrying about documentation overhead. What it's NOT: Not a DevOps tutorial - it's a productivity framework for AI-assisted development.
Why This MCP Server?
Solves the CLAUDE.md Bloat Problem
Tired of maintaining massive CLAUDE.md files (1000+ lines) across multiple projects? This MCP centralizes reusable DevOps instructions for engineers working on multiple PoCs, eliminating repeated instructions across projects and folders.
The Problem:
- ❌ Large CLAUDE.md files eat up context window
- ❌ Same practices duplicated across every project
- ❌ Reinventing TRACKER.md, ISSUES.md, docs, SoPs for every PoC
- ❌ Inconsistent standards across projects
- ❌ Context wasted on instructions instead of actual work
The Solution:
- ✅ Pre-built structure - Templates for TRACKER, ISSUES, docs, SoPs
- ✅ Focus on work - Not on "how should I document this?"
- ✅ Consistency - Same standards across all your PoCs
- ✅ Team alignment - Same patterns enable seamless collaboration and easy handovers across sessions, systems, and team members
- ✅ Faster startup - Copy template, start working
- ✅ Context saved - No bloated CLAUDE.md files
What you get (structure, not knowledge):
- 📋 TRACKER.md template - Start tracking immediately, don't design tracking
- 🐛 ISSUES.md system - Start logging issues, don't setup Jira
- 📚 Documentation standards - Start writing docs, don't debate structure
- 📖 Runbook templates - Start documenting ops, don't create SoP formats
- 🔄 Session continuity - Start handoffs, don't design handoff protocols
When searching "devops" in the MCP Registry (as of February 2026), this is the only result. While other MCPs focus on:
- 🔧 Development tools (code generation, testing, debugging)
- 📊 Data analysis (databases, APIs, analytics)
- 🎨 Content creation (writing, design, media)
This MCP provides:
- 🏗️ Configuration structure - How to organize configs per environment, generate new env configs from completed ones, create and validate SoPs
- 📚 Documentation patterns - TRACKER, ISSUES, docs, runbook templates ready to copy
- 🔄 Operations templates - Session handoff, runbook formats, documentation standards
- 🎯 Structured guidance - GG-SS organized practices for quick discovery
What makes it different:
- Prescriptive, not generative - Provides proven practices, not generated code
- Infrastructure-first - Built for ops teams, not developers
- Reusable patterns - Templates and standards across all your projects
- AI-native design - Organized for Claude to query and apply contextually
- R&D optimized - Accelerates proof-of-concept development and experimentation
Perfect for: DevOps engineers using Claude Code (VS Code plugin) to build PoCs and conduct R&D with AI assistance.
How It Works
No server management required:
- ✅ Auto-start: Spawns when Claude Code/Desktop starts
- ✅ Background: Runs silently while you work
- ✅ On-demand: Claude queries practices as needed
- ✅ Auto-stop: Shuts down when Claude closes
- ✅ Fallback: Access practices via GitHub/local if MCP unavailable (see Troubleshooting)
Configuration Options:
You can configure the MCP server globally (all projects) or per-project:
Option 1: Global Configuration (~/.claude.json)
Option 2: Project-Level Configuration (.mcp.json in project root)
Setup Steps:
- Install the MCP server (see Installation section below)
- Add configuration to
~/.claude.json(global) or.mcp.json(per-project) - Restart Claude Code/Desktop
- MCP server runs automatically - no manual startup needed
Note: The -u flag and PYTHONUNBUFFERED ensure real-time logging for debugging.
What This Provides
This MCP server provides shared DevOps practices that are common across infrastructure projects:
Available Practices (11)
Organized using GG-SS prefix pattern (Group-Sequence) for better discoverability:
Naming Pattern: GG-SS-practice-name
- GG = Group ID (01-04) - Functional category
- SS = Sequence ID (01-03) - Order within group
- Example:
03-02-air-gapped-workflow= Group 03, Sequence 02
Group Legend:
- 01 = Workflow & Processes (how to work effectively)
- 02 = Version Control & Project Management (git, issues)
- 03 = Infrastructure & Configuration (K8s, deployments, config)
- 04 = Documentation Standards (docs, READMEs, runbooks)
Group 01: Workflow & Processes
- 01-01-session-continuity - State tracking, handoff protocols, CURRENT-STATE.md
- 01-02-task-tracking - TRACKER.md, CURRENT-STATE.md, PENDING-CHANGES.md
- 01-03-efficiency-guidelines - When to script vs copy-paste, batching commands
Group 02: Version Control & Project Management
- 02-01-git-practices - Using
git mv, commit conventions, backup protocols, GitLab Flow - 02-02-issue-tracking 🆕 - In-repository Jira-like issue tracking system (Advanced)
Group 03: Infrastructure & Configuration
- 03-01-configuration-management ⭐ - Config organization, placeholders, environment isolation
- 03-02-air-gapped-workflow - Working across laptop, CloudShell, bastion, and EKS
- 03-03-standard-workflow - Common operational patterns and workflows
Group 04: Documentation Standards
- 04-01-documentation-standards - HOW/WHAT/WHY structure, naming conventions
- 04-02-readme-maintenance ⭐ - Directory documentation standards and best practices
- 04-03-runbook-documentation ⭐ - Mandatory session log standards and requirements
Available Templates (7)
- TRACKER.md - Task tracking template (milestones)
- CURRENT-STATE.md - Session handoff template
- CLAUDE.md - Simplified project instructions template
- RUNBOOK.md ⭐ - Session log template with all required sections
- ISSUE.md 🆕 - Individual issue template (Advanced)
- ISSUES.md 🆕 - Issue index template with stats dashboard (Advanced)
- issues/README.md 🆕 - How to use the issue system (Advanced)
Architecture
MCP Tools
The MCP server provides 5 tools for Claude to query practices and templates:
Template Variable Substitution
Templates support ${VARIABLE} placeholders that are automatically substituted:
Auto-provided variables:
${DATE}- Current date (YYYY-MM-DD format)${TIMESTAMP}- UTC timestamp (YYYYMMDDTHHMMz format)${USER}- Current system user${YEAR}- Current year
Custom variables: Pass any additional variables when rendering:
All ${...} placeholders in the template are replaced with provided values.
CI/CD Pipeline
This repository includes a GitHub Actions pipeline (.github/workflows/ci.yml) that automatically validates changes:
Pipeline Jobs
On every merge request and commit to main/develop:
- health-check - Runs the comprehensive health check script
- python-validation - Validates Python syntax and dependencies
- practice-validation - Ensures all practice files exist
- template-validation - Ensures templates contain variable placeholders
- link-checker - Checks documentation cross-references
Benefits
- ✅ Prevents breaking changes from reaching main branch
- ✅ Catches missing files or syntax errors automatically
- ✅ Ensures consistent quality standards
- ✅ No manual validation needed
Pipeline Status
Check pipeline status in GitHub:
- Green checkmark ✅ - All checks passed, safe to merge
- Red X ❌ - Checks failed, review errors before merging
Documentation
Quick Reference
- PRACTICE-INDEX.md - Quick lookup guide for which practice to use when
- Organized by task type (deploying, documenting, troubleshooting, etc.)
- Common scenarios with recommended practices
- Practice dependencies and relationships
Migration Guide
- MIGRATION-GUIDE.md - Roll out MCP to existing projects
- Step-by-step migration from monolithic CLAUDE.md
- Configuration setup for Claude Desktop/Code
- Testing and validation procedures
- Rollback plan if needed
Version History
- CHANGELOG.md - Complete version history and upgrade guides
- Version 1.0.0 (2026-02-13): 10 practices, 4 templates, health check tool
- Version 0.1.0 (2026-02-13): Initial release
Health Check
- health-check.sh - Validate MCP server before deployment
- 14 comprehensive checks (directory structure, files, Python environment, loading tests)
- Colored output with pass/fail counts
- Exit codes: 0 (healthy), 1 (unhealthy)
Usage:
How Projects Use This
Project CLAUDE.md Structure
Each project has a simplified CLAUDE.md:
Benefits
- DRY: Shared practices written once, used everywhere
- Consistency: All projects follow same standards
- Maintainability: Update once, all projects benefit
- Discoverability: Claude can query practices when needed
- Resilient: Fallback to GitHub/local/appendix if MCP unavailable
Template: See CLAUDE-template.md for full structure including fallback appendix
Installation & Setup
🔧 Manual Installation (Most Stable - Recommended for Development)
Best for: Developers, contributors, or anyone who wants full control
1. Clone Repository
2. Install Dependencies
3. Configure MCP Server
Edit ~/.claude/config.json:
4. Restart Claude Code/Desktop
5. Verify MCP Connection
Ask Claude: "Can you list the available DevOps practices from the MCP server?"
💡 Tip: Claude may need a reminder to check the MCP. If it doesn't respond with practice names, try:
- "Please verify you can access the devops-practices MCP server"
- "List all available MCP tools"
- Restart Claude Code again
🧪 Experimental / Testing (For Nerds)
⚠️ Note: These methods are experimental and not yet fully tested. Use Manual Installation (above) for reliable setup.
Option 1: MCP Registry via Claude Desktop UI (Experimental):
- Open Claude Desktop
- Go to Settings → Developer → MCP Servers
- Search for "devops-practices"
- Click "Install"
- Restart Claude Code/Desktop
Option 2: Install via uvx (✨ Recommended - automatic venv):
Why recommended: uvx automatically manages the virtual environment for you - no setup needed.
Option 3: Install with uv + venv (For Python developers):
Why use this: Full control over the virtual environment with modern uv tooling.
Option 4: Install to user directory (Legacy - no venv):
Option 5: Install system-wide (Requires sudo):
Option 6: Manual configuration (Edit config files directly):
Install via pip or uvx, then edit ~/.claude/config.json:
Real-World Use Cases
1. Multi-Environment Kafka Deployment
Scenario: Deploying Kafka across dev → test → uat → prod
Without MCP:
- Duplicate 580-line CLAUDE.md in each project
- Repeat same issues on each environment (12 hours total)
- No standardized approach across teams
With MCP:
- Claude queries
get_practice("configuration-management")for installation SOPs - Copies dev runbook for test environment (56% time savings)
- All teams follow same standards automatically
Result: 5.25 hours vs 12 hours (56% faster)
2. Standardized Git Workflow
Scenario: Team needs consistent branching strategy
Without MCP:
- Each project has different branching approach
- New team members confused about workflow
- Git practices documented differently everywhere
With MCP:
- Claude queries
get_practice("02-01-git-practices") - Everyone gets same 200+ line GitLab Flow documentation
- Single source of truth for git standards
Result: Consistent workflow across all 15 projects
3. Air-Gapped Infrastructure Deployment
Scenario: Deploying to secure environment without internet
Without MCP:
- Re-explain workflow every session
- Copy-paste commands from old runbooks
- Inconsistent file transfer procedures
With MCP:
- Claude queries
get_practice("air-gapped-workflow") - Gets step-by-step: Laptop → S3 → Bastion → Target
- Consistent process every time
Result: Zero security incidents, predictable deployments
4. Project Documentation Setup
Scenario: Starting new infrastructure project
Without MCP:
- Create CLAUDE.md from scratch (2 hours)
- Copy-paste from old projects (inconsistent)
- Miss important practices
With MCP:
Result: 15 minutes vs 2 hours (88% faster)
5. Issue Tracking for Complex Projects
Scenario: Managing 50+ work items across 3-month project
Without MCP:
- Use external Jira (access issues, overhead)
- Or track in scattered markdown files
- No consistent format
With MCP:
- Claude queries
get_template("ISSUES") - Creates in-repo issue tracking with dashboard
- Uses
tools/issue-manager.shfor CLI management
Result: Git-based tracking, no external dependencies
Usage Examples
For Claude
When working on your projects:
Query Practice:
Get Template (Raw):
Render Template (With Variables):
Updating Practices
For Contributors:
Branching Strategy
This repository uses GitLab Flow with semantic versioning to ensure stability for dependent projects.
Branch Structure
Branch Types
Why GitLab Flow?
- ✅ Stability:
mainalways contains tested, production-ready code - ✅ Safety: Changes go through
developbefore reaching production - ✅ Testing: CI/CD validates all changes before merge
- ✅ Versioning: Clear semantic version releases (v1.0.0, v1.1.0, etc.)
- ✅ Traceability: Full history of what changed and when
Quick Workflows
Add New Practice/Template:
Create Release:
Critical Hotfix:
Full Documentation: See CONTRIBUTING.md and git-practices.md
Governance
Who Maintains This
- Owner: Uttam Jaiswal Lead
- Contributors: DevOps Engineers
- Review Process: PR required for changes
Update Protocol
For New Practices/Templates:
- Create feature branch from
develop - Update practice or template files
- Run health check:
bash health-check.sh - Update documentation (README.md, PRACTICE-INDEX.md)
- Create PR with description →
develop - Code review by team
- Merge to
developafter CI/CD passes
For Releases:
- Create release branch from
develop:release/v1.x.0 - Update CHANGELOG.md and version numbers
- Create PR →
main - Tag release after merge:
git tag v1.x.0 - Merge release back to
develop - Announce to team (affects all dependent projects)
For Critical Fixes:
- Create hotfix branch from
main:hotfix/issue-name - Fix issue and test thoroughly
- Create PR →
main(fast-track approval) - Tag hotfix release:
git tag v1.x.1 - Merge to
developto keep in sync - Announce urgent fix to team
See: CONTRIBUTING.md for detailed workflows
Versioning
- Major version (2.0): Breaking changes to structure
- Minor version (1.1): New practices added
- Patch version (1.0.1): Clarifications, fixes
Projects Using This MCP Server
Development
See CONTRIBUTING.md for detailed contribution workflow, branching strategy, and code review process.
Adding a New Practice
- Create markdown file in
practices/ - Use clear structure with examples
- Update
mcp-server.pyif needed - Test with Claude
- Update this README (practice count)
- Update PRACTICE-INDEX.md (add to scenario lists)
- Update CHANGELOG.md (document the addition)
- Run health check:
bash health-check.sh
Adding a New Template
- Create template file in
templates/ - Use placeholders:
${PROJECT_NAME},${DATE}, etc. (see auto-provided variables in MCP Tools section) - No code changes needed -
render_templatehandles all${...}substitutions automatically - Test template:
render_template("your-template", {"VAR": "value"}) - Update this README (template count)
- Update CHANGELOG.md (document the addition)
- Run health check:
bash health-check.sh
Making Changes
- Before release: Run health check to validate all files
- After changes: Update CHANGELOG.md with version bump
- Breaking changes: Update MIGRATION-GUIDE.md with migration notes
- New features: Update PRACTICE-INDEX.md with usage scenarios
Troubleshooting
Claude Can't Access MCP Server
Symptoms: Claude doesn't return practices when asked, or acts like MCP doesn't exist
Solutions:
- Remind Claude explicitly: "Please check the devops-practices MCP server and list available practices"
- Verify MCP is loaded: Ask "What MCP servers do you have access to?"
- Check configuration: Verify
~/.claude/config.jsonhas correct paths (must be absolute paths) - Restart Claude Code: MCP servers load on startup
- Check logs: Look at
~/.cache/claude/mcp-devops-practices.logfor errors - Verify MCP process: Run
ps aux | grep mcp-server.pyto confirm it's running
💡 Pro Tip: Claude sometimes "forgets" to check MCP servers. Explicitly remind it to verify the MCP before proceeding with tasks.
Log location: ~/.cache/claude/mcp-devops-practices.log
MCP Server is Down or Unavailable
Symptoms: MCP server process crashed, not responding, or cannot start
Fallback Options:
Option 1: GitHub Practices (Recommended)
Option 2: Local Clone
Option 3: CLAUDE.md Appendix
Prevention:
- Use .mcp.json for project-level config (more reliable)
- Add MCP health check to pre-session checklist
- Keep local clone updated:
git pull origin main - Monitor logs:
tail -f ~/.cache/claude/mcp-devops-practices.log
Related: MIGRATION-GUIDE.md for project-specific fallback setup
Practice File Not Found
- Verify file exists:
ls practices/ - Check filename matches exactly (case-sensitive)
- Check MCP server logs
Template Substitution Failing
- Verify placeholder syntax:
${VARIABLE} - Check template file encoding (UTF-8)
- Review mcp-server.py logs
License
MIT License - Free to use and modify
Maintained By: Uttam Jaiswal Last Updated: 2026-02-20 Version: 1.4.0
Source: README.md at commit d6362e6
Tools
0Version history
1- v1.4.0LatestSep 16, 2026
Score
50% of the applicable checks met
How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.
- Reached in the last 30 days25 pts
Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.
- Auth declared10 pts
Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.
- Tools listed15 pts
Answer tools/list without a credential, or ship a package that starts in a sandbox without one.
- DescriptionRequired15 pts
- Logo10 pts
- Documentation15 pts
- License10 pts