DevOps Practices - MCP Server

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)

{
  "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)

{
  "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

4. 02-01-git-practices - Using git mv, commit conventions, backup protocols, GitLab Flow
5. 02-02-issue-tracking 🆕 - In-repository Jira-like issue tracking system (Advanced)

Group 03: Infrastructure & Configuration

6. 03-01-configuration-management ⭐ - Config organization, placeholders, environment isolation
7. 03-02-air-gapped-workflow - Working across laptop, CloudShell, bastion, and EKS
8. 03-03-standard-workflow - Common operational patterns and workflows

Group 04: Documentation Standards

9. 04-01-documentation-standards - HOW/WHAT/WHY structure, naming conventions
10. 04-02-readme-maintenance ⭐ - Directory documentation standards and best practices
11. 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:

Tool	Description	Example
list_practices	List all available practices	Returns list of 10 practices
get_practice	Get practice content by name	get_practice("01-02-task-tracking")
list_templates	List all available templates	Returns list of 4 templates
get_template	Get template content by name	get_template("TRACKER-template")
render_template	Render template with variable substitution	render_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:

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:

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

---

How Projects Use This

Project CLAUDE.md Structure

Each project has a simplified CLAUDE.md:

# 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

# Clone to recommended location
git clone https://github.com/ai-4-devops/devops-practices.git ~/.mcp-servers/devops-practices
cd ~/.mcp-servers/devops-practices

2. Install Dependencies

# Using uv (10-100x faster)
curl -LsSf https://astral.sh/uv/install.sh | sh
uv pip install -r requirements.txt

# Or using traditional pip
pip install -r requirements.txt

3. Configure MCP Server

Edit ~/.claude/config.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):

# 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):

# Install uv if you don't have it
curl -LsSf https://astral.sh/uv/install.sh | sh

# Create virtual environment
uv venv ~/.venvs/devops-practices-mcp

# Activate venv
source ~/.venvs/devops-practices-mcp/bin/activate

# Install MCP server
uv 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):

# Install using pip (to ~/.local/)
pip install --user devops-practices-mcp

# Add to Claude configuration
claude mcp add devops-practices -- python3 -m devops_practices_mcp

# Restart Claude Code/Desktop to activate

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

# Install system-wide (requires root)
sudo pip install devops-practices-mcp

# Add to Claude configuration
claude 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:

{
  "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:

cd devops-practices-mcp
vim practices/documentation-standards.md
# Make changes
git add practices/documentation-standards.md
git 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, templates
release/*       ← Version preparation (v1.2.0)
hotfix/*        ← Critical production fixes

Branch Types

Branch	Purpose	Created From	Merges To
main	Production releases (tagged)	-	-
develop	Active development	main	main (via release)
feature/*	New functionality	develop	develop
release/*	Version preparation	develop	main + develop
hotfix/*	Critical fixes	main	main + 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:

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

Create Release:

git checkout develop
git 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:

git checkout main
git 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

Project	Purpose	Location
kafka-deployment	Apache Kafka deployment	Example project
observability-stack	Observability stack	Example project
network-infra	Network infrastructure	Example 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

# Access practices from local clone
ls ~/.mcp-servers/devops-practices-mcp/practices/

# Read practice directly
cat ~/.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 appendix
with 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