PluginBench
MCP Server
Stale
MIT

MCP Skills Server MCP Server

io.github.srprasanna/mcp-skills-server

Dynamically load and serve custom skills from a mounted directory with hot-reload support for Claude and MCP clients.

What is the MCP Skills Server MCP server?

The MCP Skills Server is a Model Context Protocol server that discovers, loads, and exposes skills from a mounted directory with automatic hot-reloading. It enforces a strict folder structure where each skill is defined in its own directory with a SKILL.md file, enabling dynamic skill management without server restarts.

This server lets you organize custom skills in a directory structure and automatically expose them to Claude and other MCP clients. Each skill is a folder containing a SKILL.md file with YAML frontmatter and Markdown content. The server detects changes to skill files and reloads them in real time, making it ideal for iterative skill development and production deployments via Docker.

How to install MCP Skills Server

Copy-paste configuration for popular MCP clients.

transport: stdio
Config generated by PluginBench — verify against the source before use.
Environment / auth
  • MCP_SKILLS_DIR

    Root directory containing skill folders

  • MCP_SKILLS_HOT_RELOAD

    Enable automatic reloading when SKILL.md files change

  • MCP_SKILLS_LOG_LEVEL

    Logging verbosity: DEBUG, INFO, WARNING, ERROR, CRITICAL

~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "mcp-skills-server": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "docker.io/srprasanna/mcp-skills-server:1.0.0"
      ],
      "env": {
        "MCP_SKILLS_DIR": "<YOUR_MCP_SKILLS_DIR>",
        "MCP_SKILLS_HOT_RELOAD": "<YOUR_MCP_SKILLS_HOT_RELOAD>",
        "MCP_SKILLS_LOG_LEVEL": "<YOUR_MCP_SKILLS_LOG_LEVEL>"
      }
    }
  }
}

Tools & capabilities

Tools this server exposes to the agent.

  • search_skills — Search for skills by query, category, tag, or complexity level.
  • reload_skills — Manually trigger a reload of all skills from the directory.
  • get_skill_info — Get metadata for a specific skill without loading full content.
  • list_skill_folders — List all valid skill folders found in the skills directory.

Use cases

  • Organize and version-control reusable Claude skills in a Git repository
  • Develop skills iteratively with hot-reload feedback without restarting the server
  • Create a searchable catalog of skills by category, tag, and complexity for team use
  • Deploy custom skills to Claude Desktop or other MCP clients via Docker
  • Manage dependencies and examples for each skill in a standardized folder structure

MCP Skills Server MCP server FAQ

What is the MCP Skills Server?

It's an MCP server that loads skills from a mounted directory and exposes them to Claude. Each skill is a folder containing a SKILL.md file with metadata and content. The server supports hot-reloading, so changes are detected automatically.

Is it free?

Yes, the MCP Skills Server is open source under the MIT License and free to use.

How do I install it in Claude Desktop?

Add it to your claude_desktop_config.json with a Docker or Poetry command that mounts your skills directory. For Docker: use `docker run -v ${HOME}/claude-skills:/skills:ro mcp-skill-hub`. For Poetry: set MCP_SKILLS_DIR and run `poetry run mcp-skills`.

What is the required folder structure?

Each skill must be in its own dedicated folder with a SKILL.md file inside. For example: `/skills/my-skill/SKILL.md`. Loose SKILL.md files or hidden folders (starting with . or _) are ignored.

Does it require authentication?

No, the MCP Skills Server does not require authentication. It reads skills from a local mounted directory.

Can I use it with Docker?

Yes, Docker is the recommended deployment method. Use `docker run -v /path/to/skills:/skills:ro mcp-skill-hub` to run it. A docker-compose.yml is also provided for easier setup.

README (reference)

Source of truth, from the repository.

MCP Skills Server

Python 3.13+ Poetry License: MIT MCP Registry Docker Docker Pulls

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

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
  1. 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
  1. 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
  1. Create your skills directory:
mkdir -p ~/claude-skills/my-first-skill
# Create SKILL.md as shown above
  1. 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_:

VariableDefaultDescription
MCP_SKILLS_DIR/skillsRoot directory containing skill folders
MCP_SKILLS_HOT_RELOADtrueEnable automatic reloading
MCP_SKILLS_DEBOUNCE_DELAY0.5Delay (seconds) before reload
MCP_SKILLS_LOG_LEVELINFOLog level (DEBUG, INFO, WARNING, ERROR)
MCP_SKILLS_SCAN_DEPTH1Scan depth (always 1)

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:

    git checkout -b feature/my-feature
    
  2. Make changes and test:

    poetry run pytest
    poetry run mypy src
    
  3. Format and lint:

    poetry run black .
    poetry run ruff check .
    
  4. Commit and push:

    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:
    /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. 🎯

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