Transform any AI agent into a domain expert by giving it access to modular, reusable skills through the Model Context Protocol.
Inspired by Claude Skills: This MCP server brings Claude's Skills pattern to any MCP-compatible agent.
- What: An MCP server that brings Claude's Skills format to any MCP-compatible agent
- Why: Create skills once, use them everywhere—across Claude, VS Code, Cursor, and any MCP tool
- How: Point the server at your skills directory and agents discover them automatically
The fastest way to get started is with npx. Choose your platform:
Claude Code
Create .mcp.json
in your project or ~/.claude.json
globally:
{
"mcpServers": {
"skills-mcp": {
"type": "stdio",
"command": "npx",
"args": ["-y", "skills-mcp", "-s", "/absolute/path/to/skills"]
}
}
}
Claude for Desktop
Create ~/Library/Application Support/Claude/claude_desktop_config.json
:
{
"mcpServers": {
"skills-mcp": {
"command": "npx",
"args": ["-y", "skills-mcp", "-s", "/absolute/path/to/skills"]
}
}
}
Cursor
Create .cursor/mcp.json
in your project or ~/.cursor/mcp.json
globally:
{
"mcpServers": {
"skills-mcp": {
"command": "npx",
"args": ["-y", "skills-mcp", "-s", "/absolute/path/to/skills"]
}
}
}
VS Code
Create .vscode/mcp.json
in your project:
{
"servers": {
"skills-mcp": {
"type": "stdio",
"command": "npx",
"args": ["-y", "skills-mcp", "-s", "/absolute/path/to/skills"]
}
}
}
Replace /absolute/path/to/skills
with your actual skills directory path.
- Start the MCP server in your agent
- Recommended: Run the
/init-skills
prompt at the start of each session to provide background guidance on the Skills MCP workflow - Alternative: Simply ask the agent to complete a task—it will discover and use skills when needed
That's it! Your agent can now discover and use skills.
Want to try it out with ready-made skills? Anthropic maintains a collection of example skills that you can bring into your project instantly using npx degit
:
# Get the skill creator skill
npx degit anthropics/skills/skill-creator skills/skill-creator
# Get the MCP builder skill
npx degit anthropics/skills/mcp-builder skills/mcp-builder
These commands will download the skills directly into your skills/
directory without any git history. Browse the Anthropic skills repository to see all available examples.
Want Skills MCP guidance always available in your agent's context? Export the instructions:
Recommended: Use AGENTS.md
for broad agent support:
npx -y skills-mcp instructions >> AGENTS.md
For agents without AGENTS.md
support:
# Claude Code
npx -y skills-mcp instructions >> CLAUDE.md
- Use instructions export if you want skills guidance always present in every conversation
- Use
/init-skills
prompt if you want to minimize context usage and only load guidance when needed
Both approaches use the same content—choose based on your preference for context management.
What are Skills?
Skills are modular, self-contained packages that transform general-purpose AI agents into specialized experts. Think of them as "onboarding guides" for specific domains or tasks—they provide procedural knowledge that no model can fully possess.
Example: A PDF Processing Skill might include:
- Instructions for extracting text and filling forms
- Python scripts for reliable PDF operations
- Reference documentation for advanced use cases
- Template files for generating documents
Instead of explaining PDF processing in every conversation, you install the skill once and the agent knows when and how to use it.
Why Skills MCP?
While Claude has native Skills support built-in, this MCP server brings that same capability to other agents:
- Universal compatibility: Any MCP-compatible agent can now use Claude Skills
- Unified management: Single skills directory works across all agents and platforms
- Optional for Claude: When using Claude Desktop or Claude Code, you can disable this server and use native Skills instead
- Progressive disclosure: Skills load information in stages, minimizing context usage
Key benefit: Create skills once in Claude's format, use them everywhere—whether with Claude's native support or via MCP in VS Code, Cursor, and other tools.
How Skills Work
Skills use a three-level progressive disclosure system to manage context efficiently:
- Metadata (~100 tokens): Name and description loaded at startup
- Instructions (~5k tokens): Main SKILL.md content loaded when skill is triggered
- Resources (loaded as needed): References, scripts, and assets accessed on-demand
This means you can install dozens of skills without context penalty—agents only load what they need, when they need it.
Quick Start: Basic Skill Structure
Skills follow Anthropic's convention-based format from Claude Skills:
skill-name/
├── SKILL.md # Required: Skill metadata and instructions
├── references/ # Optional: Documentation loaded as needed
├── scripts/ # Optional: Executable code
└── assets/ # Optional: Templates and files for output
---
name: Skill Name
description: What this skill does and when to use it (be specific!)
---
# Skill Name
## Instructions
[Step-by-step guidance for the agent]
## Examples
[Concrete usage examples]
Tips for writing good skills:
- Make descriptions specific about WHEN to use the skill
- Use imperative/infinitive form in instructions ("To do X, use Y")
- Keep SKILL.md under 5k words; move detailed docs to
references/
- Bundle scripts for deterministic operations
- Include templates in
assets/
for files used in output
For more details, see the Skills specification.
Command Line Options
-s, --skills-dir
: Path to skills directory (required, can be specified multiple times, must be absolute paths)
When specifying multiple skills directories, all directories are scanned for skills. If multiple skills with the same ID are found across different directories, a warning will be logged and the last loaded skill will be used.
Example configuration with multiple directories:
{
"servers": {
"skills-mcp": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"skills-mcp",
"-s",
"/path/to/skills1",
"-s",
"/path/to/skills2"
]
}
}
}
You can test the server manually using stdio:
npx skills-mcp --skills-dir /absolute/path/to/skills
The server will start and wait for JSON-RPC messages on stdin. Press Ctrl+C
to stop the server.
Security Considerations
A malicious skill can:
- Direct agents to invoke tools in harmful ways
- Execute code with the agent's privileges
- Access or expose sensitive data
Treat skills like software installation: Only install from trusted sources, especially in production systems with access to sensitive data or critical operations.
For more details, see the Security Considerations section in the spec.
Available Tools
Lists all available skills with their metadata.
Output:
{
"skills": [
{
"id": "pdf-processing",
"name": "PDF Processing",
"description": "Extract text and tables from PDF files..."
}
]
}
Retrieves the full skill content and absolute path.
Input:
{
"id": "pdf-processing"
}
Output:
{
"path": "/Users/username/.claude/skills/pdf-processing/SKILL.md",
"name": "PDF Processing",
"description": "Extract text and tables...",
"content": "# PDF Processing\n\n## Quick start\n..."
}
Available Prompts
Provides informational guidance about the Skills MCP workflow. This prompt:
- Explains what skills are and how they're structured
- Outlines the progressive disclosure model (load only what you need, when you need it)
- Describes the step-by-step workflow for discovering, loading, and using skills
- Clarifies that the MCP is a minimal wrapper—agents handle all file operations
When to use: Run at the start of a conversation to provide background context. The prompt is informational only—it doesn't trigger any immediate actions. Agents will use skills when they encounter tasks that match available skill descriptions.
How It Works
The Skills MCP follows a minimal wrapper design that leverages the full capabilities of modern AI agents:
What the server provides:
- Skill discovery and metadata
- Skill content with absolute file paths
- Skills-specific context formatting
What agents handle (using their existing tools):
- Reading referenced files (
references/
,scripts/
,assets/
) - Executing scripts
- Searching and navigating directories
Example workflow:
- Agent calls
list_skills
and finds "PDF Processing" - Agent calls
get_skill
and receives/path/to/pdf-processing/SKILL.md
- Skill mentions
references/FORMS.md
for advanced features - Agent constructs full path and reads it:
/path/to/pdf-processing/references/FORMS.md
- Agent executes scripts:
cd /path/to/pdf-processing && python scripts/fill_form.py
This design keeps the MCP server simple while giving agents maximum flexibility.
- Claude Skills: The original Skills format this server implements
- Full Specification: Complete technical specification and design rationale
- Model Context Protocol: Learn about MCP