Devops Practices

io.github.ai-4-devops由 GitHub 帳號 ai-4-devops 發布v1.4.0更新於 Nov 10, 2026

Productivity framework for DevOps engineers using AI assistance (Claude Code) while working on PoCs

已驗證STDIO僅桌面知識與記憶開發者工具

概覽

AI 產生的概覽

為助理提供可查詢的 DevOps 實務文件與專案檔案範本庫,用於 AI 輔助的基礎架構工作。

可以做什麼
提供 11 份共用 DevOps 實務文件(工作階段延續、任務追蹤、Git 實務、設定管理、氣隙工作流程、文件與執行手冊標準)以及 7 個檔案範本,例如 TRACKER、CURRENT-STATE、RUNBOOK 和 CLAUDE。工具包含 list_practices、get_practice、list_templates、get_template 與 render_template,後者可替換 DATE、TIMESTAMP、USER、YEAR 等佔位符及自訂變數。內容屬於規範性參考資料,而非產生的程式碼。
適用情境
適合以 AI 助理進行概念驗證或研發工作的 DevOps 工程師,希望在多個專案間維持一致的文件、追蹤與執行手冊結構,而不必重複維護冗長的指示檔案。當同一套標準需要套用到多個程式碼儲存庫時最為有用。
執行需求
以 Python 套件(devops-practices-mcp)形式透過 stdio 在本機執行,使用 python3 啟動;README 也提供 uvx 或虛擬環境的安裝方式。需要安裝 Python 及其相依套件,並在助理的 MCP 設定檔中進行設定。未宣告任何帳號、API 金鑰或環境變數。
安裝前請注意
此伺服器只讀取內附的實務與範本檔案,但 render_template 會產生替換後的內容,助理可能據此建立專案檔案。README 中的安裝說明包含複製儲存庫與執行 shell 安裝指令碼,執行前請先檢視這些步驟。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Devops Practices,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

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)

json
{  "mcpServers": {    "devops-practices": {      "command": "python3",      "args": ["-u", "~/.mcp-servers/devops-practices/mcp-server.py"],      "env": {"PYTHONUNBUFFERED": "1"}    }  }}

Option 2: Project-Level Configuration (.mcp.json in project root)

json
{  "mcpServers": {    "devops-practices": {      "command": "python3",      "args": ["-u", "~/.mcp-servers/devops-practices/mcp-server.py"],      "env": {"PYTHONUNBUFFERED": "1"}    }  }}

Setup Steps:

  1. Install the MCP server (see Installation section below)
  2. Add configuration to ~/.claude.json (global) or .mcp.json (per-project)
  3. Restart Claude Code/Desktop
  4. 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
  1. 01-01-session-continuity - State tracking, handoff protocols, CURRENT-STATE.md
  2. 01-02-task-tracking - TRACKER.md, CURRENT-STATE.md, PENDING-CHANGES.md
  3. 01-03-efficiency-guidelines - When to script vs copy-paste, batching commands
Group 02: Version Control & Project Management
  1. 02-01-git-practices - Using git mv, commit conventions, backup protocols, GitLab Flow
  2. 02-02-issue-tracking 🆕 - In-repository Jira-like issue tracking system (Advanced)
Group 03: Infrastructure & Configuration
  1. 03-01-configuration-management ⭐ - Config organization, placeholders, environment isolation
  2. 03-02-air-gapped-workflow - Working across laptop, CloudShell, bastion, and EKS
  3. 03-03-standard-workflow - Common operational patterns and workflows
Group 04: Documentation Standards
  1. 04-01-documentation-standards - HOW/WHAT/WHY structure, naming conventions
  2. 04-02-readme-maintenance ⭐ - Directory documentation standards and best practices
  3. 04-03-runbook-documentation ⭐ - Mandatory session log standards and requirements

Available Templates (7)

  1. TRACKER.md - Task tracking template (milestones)
  2. CURRENT-STATE.md - Session handoff template
  3. CLAUDE.md - Simplified project instructions template
  4. RUNBOOK.md ⭐ - Session log template with all required sections
  5. ISSUE.md 🆕 - Individual issue template (Advanced)
  6. ISSUES.md 🆕 - Issue index template with stats dashboard (Advanced)
  7. issues/README.md 🆕 - How to use the issue system (Advanced)

Architecture

devops-practices-mcp/├── README.md                    # This file├── mcp-server.py                # MCP server implementation├── requirements.txt             # Python dependencies├── .github/workflows/ci.yml     # GitHub Actions pipeline├── health-check.sh              # Health validation script├── practices/                   # Shared practice documents (11 files, GG-SS organized)│   ├── 01-01-session-continuity.md│   ├── 01-02-task-tracking.md│   ├── 01-03-efficiency-guidelines.md│   ├── 02-01-git-practices.md│   ├── 02-02-issue-tracking.md  # 🆕 Advanced: In-repo issue tracking│   ├── 03-01-configuration-management.md│   ├── 03-02-air-gapped-workflow.md│   ├── 03-03-standard-workflow.md│   ├── 04-01-documentation-standards.md│   ├── 04-02-readme-maintenance.md│   └── 04-03-runbook-documentation.md├── templates/                   # File templates (7 files)│   ├── TRACKER-template.md│   ├── CURRENT-STATE-template.md│   ├── CLAUDE-template.md│   ├── RUNBOOK-template.md│   ├── ISSUE-TEMPLATE.md        # 🆕 Individual issue template│   ├── ISSUES.md                # 🆕 Issue index with dashboard│   └── issues-README.md         # 🆕 Issue system guide├── tools/                       # Automation tools 🆕│   └── issue-manager.sh         # CLI for managing issues└── config/                      # MCP configuration    └── mcp-config.json          # Server configuration

MCP Tools

The MCP server provides 5 tools for Claude to query practices and templates:

ToolDescriptionExample
list_practicesList all available practicesReturns list of 10 practices
get_practiceGet practice content by nameget_practice("01-02-task-tracking")
list_templatesList all available templatesReturns list of 4 templates
get_templateGet template content by nameget_template("TRACKER-template")
render_templateRender template with variable substitutionrender_template("TRACKER-template", {"PROJECT_NAME": "my-project"})

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:

python
render_template("RUNBOOK-template", {    "SESSION_NUMBER": "1",    "TITLE": "Kafka Deployment",    "CLUSTER_NAME": "example-eks-uat",    "OBJECTIVE_DESCRIPTION": "Deploy Kafka cluster to UAT"})

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:

  1. health-check - Runs the comprehensive health check script
  2. python-validation - Validates Python syntax and dependencies
  3. practice-validation - Ensures all practice files exist
  4. template-validation - Ensures templates contain variable placeholders
  5. 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:

bash
cd devops-practices-mcpbash health-check.sh

How Projects Use This

Project CLAUDE.md Structure

Each project has a simplified CLAUDE.md:

markdown
# Claude AI Assistant - [Project Name]
## MCP Service Integration**Shared Practices**: `devops-practices` MCP server
Claude has access to shared DevOps practices via MCP:- Air-gapped workflow- Documentation standards- Session continuity protocols- Task tracking guidelines- Git best practices- Efficiency guidelines
⚠️ Fallback: If MCP unavailable, see Appendix or GitHub practices
## Project-Specific: [Project Details][Only project-specific instructions here]
## Appendix: Critical Practices (Fallback)[Emergency practice summaries if MCP down - see CLAUDE-template.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
bash
# Clone to recommended locationgit clone https://github.com/ai-4-devops/devops-practices.git ~/.mcp-servers/devops-practicescd ~/.mcp-servers/devops-practices
2. Install Dependencies
bash
# Using uv (10-100x faster)curl -LsSf https://astral.sh/uv/install.sh | shuv pip install -r requirements.txt
# Or using traditional pippip install -r requirements.txt
3. Configure MCP Server

Edit ~/.claude/config.json:

json
{  "mcpServers": {    "devops-practices": {      "command": "python3",      "args": ["-u", "~/.mcp-servers/devops-practices/mcp-server.py"],      "env": {"PYTHONUNBUFFERED": "1"}    }  }}
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):

  1. Open Claude Desktop
  2. Go to Settings → Developer → MCP Servers
  3. Search for "devops-practices"
  4. Click "Install"
  5. Restart Claude Code/Desktop

Option 2: Install via uvx (✨ Recommended - automatic venv):

bash
# Add MCP server using uvx (handles venv automatically)claude mcp add devops-practices -- uvx devops-practices-mcp
# Restart Claude Code/Desktop to activate

Why recommended: uvx automatically manages the virtual environment for you - no setup needed.

Option 3: Install with uv + venv (For Python developers):

bash
# Install uv if you don't have itcurl -LsSf https://astral.sh/uv/install.sh | sh
# Create virtual environmentuv venv ~/.venvs/devops-practices-mcp
# Activate venvsource ~/.venvs/devops-practices-mcp/bin/activate
# Install MCP serveruv pip install devops-practices-mcp
# Add to Claude configuration (using venv's python)claude mcp add devops-practices -- ~/.venvs/devops-practices-mcp/bin/python -m devops_practices_mcp
# Restart Claude Code/Desktop to activate

Why use this: Full control over the virtual environment with modern uv tooling.

Option 4: Install to user directory (Legacy - no venv):

bash
# Install using pip (to ~/.local/)pip install --user devops-practices-mcp
# Add to Claude configurationclaude mcp add devops-practices -- python3 -m devops_practices_mcp
# Restart Claude Code/Desktop to activate

Option 5: Install system-wide (Requires sudo):

bash
# Install system-wide (requires root)sudo pip install devops-practices-mcp
# Add to Claude configurationclaude mcp add devops-practices -- python3 -m devops_practices_mcp
# Restart Claude Code/Desktop to activate

Option 6: Manual configuration (Edit config files directly):

Install via pip or uvx, then edit ~/.claude/config.json:

json
{  "mcpServers": {    "devops-practices": {      "command": "uvx",      "args": ["devops-practices-mcp"],      "env": {}    }  }}

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:

User: "Create project structure for monitoring-stack project"Claude: [Queries MCP for templates]Claude: Creates TRACKER.md, CURRENT-STATE.md, RUNBOOK.md        All following latest standards

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.sh for CLI management

Result: Git-based tracking, no external dependencies


Usage Examples

For Claude

When working on your projects:

Query Practice:

User: "What's the air-gapped workflow for file transfers?"Claude: [Queries MCP: get_practice("air-gapped-workflow")]Claude: [Receives markdown content]Claude: "Here's the air-gapped workflow..."

Get Template (Raw):

User: "Show me the TRACKER template"Claude: [Queries MCP: get_template("TRACKER-template")]Claude: [Receives template with ${VARIABLES}]Claude: "Here's the template..."

Render Template (With Variables):

User: "Create a TRACKER.md for my kafka-deployment project"Claude: [Queries MCP: render_template("TRACKER-template", {    "PROJECT_NAME": "kafka-deployment",    "DATE": "2026-02-14",    "PHASE_NAME": "UAT Deployment"})]Claude: [Receives rendered template with all variables substituted]Claude: [Creates TRACKER.md with actual values]

Updating Practices

For Contributors:

bash
cd devops-practices-mcpvim practices/documentation-standards.md# Make changesgit add practices/documentation-standards.mdgit commit -m "Update documentation standards: add new RUNBOOKS guidelines"git push# All projects using this MCP server now get updated standards

Branching Strategy

This repository uses GitLab Flow with semantic versioning to ensure stability for dependent projects.

Branch Structure

main            ← Production releases only (v1.0.0, v1.1.0, etc.)  ↑develop         ← Active development, integration branch  ↑feature/*       ← New practices, templatesrelease/*       ← Version preparation (v1.2.0)hotfix/*        ← Critical production fixes

Branch Types

BranchPurposeCreated FromMerges To
mainProduction releases (tagged)--
developActive developmentmainmain (via release)
feature/*New functionalitydevelopdevelop
release/*Version preparationdevelopmain + develop
hotfix/*Critical fixesmainmain + develop

Why GitLab Flow?

  • ✅ Stability: main always contains tested, production-ready code
  • ✅ Safety: Changes go through develop before 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:

bash
git checkout developgit checkout -b feature/add-security-practice# Make changes, commitgit push origin feature/add-security-practice# Create PR → develop

Create Release:

bash
git checkout developgit checkout -b release/v1.2.0# Update CHANGELOG.md, version numbers# Create PR → main# Tag release: git tag v1.2.0# Merge back to develop

Critical Hotfix:

bash
git checkout maingit checkout -b hotfix/critical-bug# Fix, commit, push# Create PR → main (fast-track)# Also merge to develop

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:

  1. Create feature branch from develop
  2. Update practice or template files
  3. Run health check: bash health-check.sh
  4. Update documentation (README.md, PRACTICE-INDEX.md)
  5. Create PR with description → develop
  6. Code review by team
  7. Merge to develop after CI/CD passes

For Releases:

  1. Create release branch from develop: release/v1.x.0
  2. Update CHANGELOG.md and version numbers
  3. Create PR → main
  4. Tag release after merge: git tag v1.x.0
  5. Merge release back to develop
  6. Announce to team (affects all dependent projects)

For Critical Fixes:

  1. Create hotfix branch from main: hotfix/issue-name
  2. Fix issue and test thoroughly
  3. Create PR → main (fast-track approval)
  4. Tag hotfix release: git tag v1.x.1
  5. Merge to develop to keep in sync
  6. 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

ProjectPurposeLocation
kafka-deploymentApache Kafka deploymentExample project
observability-stackObservability stackExample project
network-infraNetwork infrastructureExample project

Development

See CONTRIBUTING.md for detailed contribution workflow, branching strategy, and code review process.

Adding a New Practice

  1. Create markdown file in practices/
  2. Use clear structure with examples
  3. Update mcp-server.py if needed
  4. Test with Claude
  5. Update this README (practice count)
  6. Update PRACTICE-INDEX.md (add to scenario lists)
  7. Update CHANGELOG.md (document the addition)
  8. Run health check: bash health-check.sh

Adding a New Template

  1. Create template file in templates/
  2. Use placeholders: ${PROJECT_NAME}, ${DATE}, etc. (see auto-provided variables in MCP Tools section)
  3. No code changes needed - render_template handles all ${...} substitutions automatically
  4. Test template: render_template("your-template", {"VAR": "value"})
  5. Update this README (template count)
  6. Update CHANGELOG.md (document the addition)
  7. 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:

  1. Remind Claude explicitly: "Please check the devops-practices MCP server and list available practices"
  2. Verify MCP is loaded: Ask "What MCP servers do you have access to?"
  3. Check configuration: Verify ~/.claude/config.json has correct paths (must be absolute paths)
  4. Restart Claude Code: MCP servers load on startup
  5. Check logs: Look at ~/.cache/claude/mcp-devops-practices.log for errors
  6. Verify MCP process: Run ps aux | grep mcp-server.py to 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)

Access practices directly from GitHub:https://github.com/ai-4-devops/devops-practices/tree/main/practices
Ask Claude to read practices via GitHub URLs when MCP unavailable.

Option 2: Local Clone

bash
# Access practices from local clonels ~/.mcp-servers/devops-practices-mcp/practices/
# Read practice directlycat ~/.mcp-servers/devops-practices-mcp/practices/03-02-air-gapped-workflow.md

Option 3: CLAUDE.md Appendix

Projects using the CLAUDE-template.md have a built-in appendixwith critical practice summaries for emergency fallback.
See: templates/CLAUDE-template.md (Appendix section)

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

  1. Verify file exists: ls practices/
  2. Check filename matches exactly (case-sensitive)
  3. Check MCP server logs

Template Substitution Failing

  1. Verify placeholder syntax: ${VARIABLE}
  2. Check template file encoding (UTF-8)
  3. 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

來源:README.md,提交 d6362e6

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  1. v1.4.0最新Sep 16, 2026

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