MCP Skills Server

A production-ready Model Context Protocol (MCP) server that dynamically loads and exposes skills from a mounted volume with hot-reloading support.

📦 Available on MCP Registry - Install with one command!

Features

• Dynamic Skill Loading: Automatically discovers and loads skills from a directory
• Hot-Reloading: Detects changes to SKILL.md files and reloads without restart
• Folder Structure Validation: Enforces best practices with clear error messages
• MCP Protocol Compliant: Full implementation of resources and tools
• Production Ready: Comprehensive error handling, logging, and validation
• Docker Support: Run in containers with volume mounting
• Type Safe: Full type hints using Python 3.13 features
• Well Tested: >80% code coverage with comprehensive test suite

Table of Contents

• Skills Directory Structure
• Quick Start
• Installation
• Usage
• Configuration
• Skill File Format
• MCP Resources and Tools
• Development
• Troubleshooting
• Contributing
• License

Skills Directory Structure

CRITICAL REQUIREMENT: Each skill MUST be in its own dedicated folder within the skills directory. The server will ONLY recognize skills that follow this structure.

✅ Valid Structure

your-skills-directory/
├── skill-one/
│   └── SKILL.md          ← Required
├── skill-two/
│   ├── SKILL.md          ← Required
│   └── examples/         ← Optional
│       └── example.py
└── skill-three/
    ├── SKILL.md
    ├── examples/
    │   └── demo.py
    └── templates/
        └── template.txt

❌ Invalid Structures (Will Be Ignored)

your-skills-directory/
├── SKILL.md                  ❌ Not in a folder - WILL BE SKIPPED
├── random-file.txt           ❌ Not a skill folder
├── .hidden-folder/           ❌ Hidden folder - WILL BE SKIPPED
│   └── SKILL.md
└── __pycache__/              ❌ System folder - WILL BE SKIPPED
    └── SKILL.md

Folder Naming Conventions

Valid folder names:

• Lowercase with hyphens: my-skill-name
• Lowercase with underscores: excel_advanced
• Alphanumeric: skill-name-v2

Invalid (will be skipped):

• Hidden folders starting with .
• Private folders starting with _
• System folders: __pycache__, node_modules, .git, etc.

Quick Start

Using Docker (Recommended)

1. Create your skills directory:

mkdir -p ~/claude-skills/my-first-skill

2. Create a skill file:

cat > ~/claude-skills/my-first-skill/SKILL.md << 'EOF'
---
name: "my-first-skill"
description: "My first Claude skill"
---

# My First Skill

This is my first skill for Claude!

## Usage

Simply describe what your skill does here.
EOF

3. Run the server:

docker run -i --rm \
  -v ~/claude-skills:/skills:ro \
  mcp-skill-hub

Using Poetry (Development)

1. Clone and install:

git clone https://github.com/srprasanna/mcp-skill-hub.git
cd mcp-skill-hub
poetry install

2. Create your skills directory:

mkdir -p ~/claude-skills/my-first-skill
# Create SKILL.md as shown above

3. Run the server:

export MCP_SKILLS_DIR=~/claude-skills
poetry run mcp-skills

Installation

Prerequisites

• Python 3.13+ (for development)
• Poetry 1.7+ (for dependency management)
• Docker (optional, for containerized deployment)

Install with Poetry

# Clone the repository
git clone https://github.com/srprasanna/mcp-skill-hub.git
cd mcp-skill-hub

# Install dependencies
poetry install

# Verify installation
poetry run mcp-skills --help

Build Docker Image

# Build the image
docker build -t mcp-skill-hub .

# Or use docker-compose
docker-compose build

Usage

Running Locally

# Set the skills directory
export MCP_SKILLS_DIR=/path/to/your/skills

# Run the server
poetry run mcp-skills

Running with Docker

docker run -i --rm \
  -v /path/to/your/skills:/skills:ro \
  -e MCP_SKILLS_LOG_LEVEL=INFO \
  mcp-skill-hub

Running with Docker Compose

# Edit docker-compose.yml to set your skills directory path
docker-compose up mcp-skills

Integrating with Claude Desktop

Add to your Claude Desktop configuration (claude_desktop_config.json):

{
  "mcpServers": {
    "skills": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-v",
        "${HOME}/claude-skills:/skills:ro",
        "mcp-skill-hub"
      ]
    }
  }
}

Or using Poetry:

{
  "mcpServers": {
    "skills": {
      "command": "poetry",
      "args": ["run", "mcp-skills"],
      "cwd": "/path/to/mcp-skill-hub",
      "env": {
        "MCP_SKILLS_DIR": "/path/to/your/skills"
      }
    }
  }
}

Important: Make sure your ${HOME}/claude-skills directory contains skill folders, not loose SKILL.md files!

Configuration

Configuration is done via environment variables with the prefix MCP_SKILLS_:

Example .env File

MCP_SKILLS_DIR=/path/to/skills
MCP_SKILLS_HOT_RELOAD=true
MCP_SKILLS_DEBOUNCE_DELAY=0.5
MCP_SKILLS_LOG_LEVEL=INFO

Skill File Format

Skills are defined in SKILL.md files with YAML frontmatter:

Minimal Example

---
name: "my-skill"
description: "Brief description"
---

# My Skill

Your skill content here in Markdown.

Complete Example

---
# Required fields
name: "excel-advanced"
description: "Advanced Excel automation techniques"

# Version and authorship
version: "1.2.0"
author: "Your Name"
created: "2025-01-15"
updated: "2025-10-23"

# Dependencies
dependencies:
  python: ["openpyxl>=3.0.0", "pandas>=2.0.0"]
  system: ["libreoffice"]

# Categorization
category: "office-automation"
tags: ["excel", "spreadsheet", "automation"]
complexity: "intermediate"  # beginner|intermediate|advanced

# Usage guidance
when_to_use:
  - "Automating Excel report generation"
  - "Processing multiple Excel files"
  - "Creating complex formulas programmatically"

# Relationships
related_skills: ["csv-processing", "data-analysis"]

# Examples
has_examples: true
example_files: ["examples/report_generator.py", "templates/report_template.xlsx"]
---

# Excel Advanced Automation

This skill covers advanced Excel automation techniques...

## Features

- Automated report generation
- Formula creation
- Bulk processing

## Examples

See `examples/report_generator.py` for a working example.

Available Metadata Fields

Required:

• name: Unique identifier (kebab-case recommended)
• description: Brief description

Optional:

• version: Semantic version
• author: Creator name
• created, updated: ISO dates (YYYY-MM-DD)
• dependencies: Python packages or system tools
• category: Main category for grouping
• tags: Array of tags for search
• complexity: beginner, intermediate, or advanced
• when_to_use: Array of usage scenarios
• related_skills: Names of related skills
• has_examples: Boolean flag
• example_files: Paths to example files (relative to skill folder)

MCP Resources and Tools

Resources

The server exposes these MCP resources:

1. skill://catalog - JSON catalog of all skills with metadata
2. skill://{name} - Individual skill markdown content

Tools

Four tools are available for interacting with skills:

1. search_skills

Search for skills by query, category, tag, or complexity.

{
  "query": "excel",
  "category": "office-automation",
  "tag": "automation",
  "complexity": "intermediate"
}

2. reload_skills

Manually trigger a reload of all skills from the directory.

{}

3. get_skill_info

Get metadata for a specific skill without loading full content.

{
  "name": "excel-advanced"
}

4. list_skill_folders

List all valid skill folders found in the skills directory.

{}

Development

Setup Development Environment

# Clone repository
git clone https://github.com/srprasanna/mcp-skill-hub.git
cd mcp-skill-hub

# Install dependencies (including dev dependencies)
poetry install

# Activate virtual environment
poetry shell

Running Tests

# Run all tests
poetry run pytest

# Run with coverage
poetry run pytest --cov=mcp_skills --cov-report=html

# Run specific test file
poetry run pytest tests/test_scanner.py

# Run with verbose output
poetry run pytest -v

Code Quality

# Format code
poetry run black .

# Lint code
poetry run ruff check .

# Type checking
poetry run mypy src

# Run all quality checks
poetry run black . && poetry run ruff check . && poetry run mypy src

Development Workflow

1. Create a branch:

   bash

   git checkout -b feature/my-feature
   

2. Make changes and test:

   bash

   poetry run pytest
   poetry run mypy src
   

3. Format and lint:

   bash

   poetry run black .
   poetry run ruff check .
   

4. Commit and push:

   bash

   git commit -m "Add feature: description"
   git push origin feature/my-feature
   

Project Structure

mcp-skill-hub/
├── src/mcp_skills/          # Source code
│   ├── models/              # Data models
│   ├── parsers/             # Skill parsers
│   ├── storage/             # Repository pattern
│   ├── scanner.py           # Directory scanning
│   ├── watcher.py           # Hot-reload watcher
│   ├── server.py            # MCP server
│   ├── config.py            # Configuration
│   └── __main__.py          # CLI entry point
├── tests/                   # Test suite
├── examples/                # Example skills
├── docs/                    # Documentation
└── pyproject.toml           # Poetry configuration

Troubleshooting

Common Issues

Skills Not Loading

Problem: No skills are loaded when the server starts.

Solution:

1. Check that your skills are in dedicated folders:
   code

   /skills/my-skill/SKILL.md  ✓
   /skills/SKILL.md           ✗
   

2. Verify folder names don't start with . or _
3. Check logs for detailed error messages

Hot-Reload Not Working

Problem: Changes to SKILL.md files aren't detected.

Solution:

1. Ensure MCP_SKILLS_HOT_RELOAD=true
2. Check file is named exactly SKILL.md
3. Verify file is in a valid skill folder
4. Look for file watcher errors in logs

Parsing Errors

Problem: SKILL.md files fail to parse.

Solution:

1. Validate YAML frontmatter syntax
2. Ensure frontmatter is between --- delimiters
3. Check required fields (name, description) are present
4. Use a YAML validator to check syntax

Validation Command

Check your skills directory structure:

poetry run mcp-skills --validate

Expected output:

✓ /skills/excel-advanced: Valid skill
✓ /skills/python-automation: Valid skill
✗ /skills/SKILL.md: Error - Skills must be in folders
✗ /skills/.hidden: Skipped - Hidden folder
⚠ /skills/empty-folder: Warning - No SKILL.md found

Summary: 2 valid, 1 error, 1 warning, 1 skipped

Logging

Enable debug logging for detailed information:

export MCP_SKILLS_LOG_LEVEL=DEBUG
poetry run mcp-skills

Logs include:

• Folder structure validation messages
• Scan progress and results
• Parse successes and failures
• Hot-reload events
• Detailed error context

Contributing

Contributions are welcome! Please see CONTRIBUTING.md for guidelines.

Quick Contributing Guide

1. Fork the repository
2. Create a feature branch
3. Make your changes with tests
4. Ensure all tests pass and code is formatted
5. Submit a pull request

Code Standards

• Python 3.13+ with type hints
• Black for formatting (88 char line length)
• Ruff for linting
• Mypy for type checking (strict mode)
• Pytest for testing (>80% coverage)

Releases

This project uses automated releases via GitHub Actions.

Creating a Release

1. Go to Actions → Release workflow
2. Click Run workflow
3. Choose version bump type:
   • patch - Bug fixes (0.1.0 → 0.1.1)
   • minor - New features (0.1.0 → 0.2.0)
   • major - Breaking changes (0.1.0 → 1.0.0)
   • Or specify exact version (e.g., 1.2.3)
4. Select Docker registry (docker.io or ghcr.io)
5. Click Run workflow

The workflow will:

• ✅ Bump version in pyproject.toml
• ✅ Create Git tag and GitHub release
• ✅ Build and push Docker image
• ✅ Run tests to verify release

Docker Images:

• Docker Hub: {username}/mcp-skill-hub:{version}
• GitHub: ghcr.io/{owner}/mcp-skill-hub:{version}

See RELEASING.md for detailed release documentation.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Built with MCP Python SDK
• Inspired by the need for dynamic skill management in Claude
• Thanks to all contributors!

Note: This server makes it impossible to misunderstand the folder structure requirement through:

• Clear error messages with folder context
• Comprehensive logging
• Validation at multiple levels
• Detailed documentation
• Working examples

Each skill MUST be in its own folder. This design decision ensures clean organization, easy management, and unambiguous structure. 🎯