How do I install the MCP Skills skill?

Run npx skillmds add majiayu000/mcp-skills in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is MCP Skills safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: docs only. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with MCP Skills?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is MCP Skills free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published MCP Skills?

majiayu000 (@majiayu000) published this skill. Their other Agent Skills are listed on their SkillMD profile.

MCP Skills by majiayu000 — Agent Skill

Name: MCP Skills
Rating: 4.2 (5 reviews)
Author: majiayu000

MCP Skills

Registry of MCP-derived skills with progressive disclosure. Use when asked about "github", "assistant-ui", "chrome-devtools", "playwright", "shadcn", "undetected-chromedriver", "logfire", "magicui", "livekit", "ToolUI", "generative UI", "chat components", "PR", "issues", "repository", "browser automation", "E2E testing", "screenshot", "console logs", "network requests", "performance tracing", "stealth browser", "bot detection bypass", "web scraping", "observability", "tracing", "exceptions", "Magic UI", "bento-grid", "animations", "voice agents", "real-time audio", "WebRTC", "UI components", "MCP tools", or any converted MCP server. Provides 90%+ context savings compared to native MCP loading.

majiayu000 3b8f3e9 2 files · 5.1 KB Updated Sep 9, 2026 567 repo stars

File contents

MCP Skills Registry

Central directory for all MCP-derived skills. Each sub-skill wraps an MCP server with progressive disclosure.

Available Skills

Skill	Tools	Trigger Keywords
assistant-ui	2	ToolUI, generative UI, chat components, assistant-ui docs
chrome-devtools	26	browser automation, E2E testing, screenshot, console, network, performance, Core Web Vitals
github	26	PR, issues, repository, commits, code search
livekit-docs	7	LiveKit, voice agents, real-time audio, WebRTC, agents SDK, rooms, tracks, Python agents
logfire	4	Pydantic Logfire, observability, tracing, exceptions, spans, logs, SQL queries
magicui	8	Magic UI, React components, animations, bento-grid, marquee, shimmer, particles
mcp-undetected-chromedriver	16	stealth browser, bot detection bypass, web scraping, anti-detection, PDF export
playwright	22	Playwright, browser testing, automation, clicks, forms, screenshots, navigation, tabs
shadcn	7	shadcn/ui, UI components, React components, Tailwind, component registry, examples, button, card, dialog, form, table, accordion, toast

See index.json for the full list, or browse sub-directories.

⚠️ These Are Skill Wrappers, NOT Native MCP Tools

You CANNOT call mcp__shadcn__*, mcp__github__*, etc. directly - those don't exist. These skills wrap MCP servers via a central executor.py.

Usage

Step 1: Read the skill's SKILL.md (from project root):

cat .claude/skills/mcp-skills/<skill-name>/SKILL.md

# Example: shadcn skill
cat .claude/skills/mcp-skills/shadcn/SKILL.md

Step 2: Use the central executor.py (from project root):

# List available skills
python .claude/skills/mcp-skills/executor.py --skills

# List tools in a skill
python .claude/skills/mcp-skills/executor.py --skill github --list

# Get tool schema
python .claude/skills/mcp-skills/executor.py --skill github --describe create_issue

# Call a tool
python .claude/skills/mcp-skills/executor.py --skill github --call '{"tool": "create_issue", "arguments": {...}}'

Context Efficiency

Scenario	Native MCP (all servers)	This Registry	Savings
Idle	40-100k tokens	~150 tokens	99%+
Using 1 skill	40-100k tokens	~5k tokens	90%+
After execution	40-100k tokens	~150 tokens	99%+

How It Works

Registry loads first - This file (~150 tokens)
User requests a tool - e.g., "create a GitHub PR"
Sub-skill loads - Only the relevant skill's SKILL.md (~4k tokens)
Executor runs - External process, 0 context tokens
Result returned - Context drops back to registry only

Adding New Skills

Use the mcp-to-skill-converter skill:

cd .claude/skills/mcp-to-skill-converter
python mcp_to_skill.py --name <server-name>
# Outputs to .claude/skills/mcp-skills/<server-name>/

Skill Structure

The registry has a central executor with per-skill configs:

.claude/skills/mcp-skills/
├── executor.py              # Central executor for ALL skills
├── SKILL.md                 # This registry file
├── index.json               # Skill metadata registry
└── <skill-name>/
    ├── SKILL.md             # Tool documentation
    ├── mcp-config.json      # Server config
    └── package.json         # Dependencies

This registry enables progressive disclosure of MCP servers as Claude Skills.

---name: mcp-skillsdescription: Registry of MCP-derived skills with progressive disclosure. Use when asked about "github", "assistant-ui", "chrome-devtools", "playwright", "shadcn", "undetected-chromedriver", "logfire", "magicui", "livekit", "ToolUI", "generative UI", "chat components", "PR", "issues", "repository", "browser automation", "E2E testing", "screenshot", "console logs", "network requests", "performance tracing", "stealth browser", "bot detection bypass", "web scraping", "observability", "tracing", "exceptions", "Magic UI", "bento-grid", "animations", "voice agents", "real-time audio", "WebRTC", "UI components", "MCP tools", or any converted MCP server. Provides 90%+ context savings compared to native MCP loading.--- # MCP Skills Registry Central directory for all MCP-derived skills. Each sub-skill wraps an MCP server with progressive disclosure. ## Available Skills | Skill | Tools | Trigger Keywords | |-------|-------|------------------| | assistant-ui | 2 | ToolUI, generative UI, chat components, assistant-ui docs | | chrome-devtools | 26 | browser automation, E2E testing, screenshot, console, network, performance, Core Web Vitals | | github | 26 | PR, issues, repository, commits, code search | | livekit-docs | 7 | LiveKit, voice agents, real-time audio, WebRTC, agents SDK, rooms, tracks, Python agents | | logfire | 4 | Pydantic Logfire, observability, tracing, exceptions, spans, logs, SQL queries | | magicui | 8 | Magic UI, React components, animations, bento-grid, marquee, shimmer, particles | | mcp-undetected-chromedriver | 16 | stealth browser, bot detection bypass, web scraping, anti-detection, PDF export | | playwright | 22 | Playwright, browser testing, automation, clicks, forms, screenshots, navigation, tabs | | shadcn | 7 | shadcn/ui, UI components, React components, Tailwind, component registry, examples, button, card, dialog, form, table, accordion, toast | See `index.json` for the full list, or browse sub-directories. ## ⚠️ These Are Skill Wrappers, NOT Native MCP Tools You CANNOT call `mcp__shadcn__*`, `mcp__github__*`, etc. directly - those don't exist. These skills wrap MCP servers via a central executor.py. ## Usage **Step 1: Read the skill's SKILL.md** (from project root): ```bash cat .claude/skills/mcp-skills/<skill-name>/SKILL.md # Example: shadcn skill cat .claude/skills/mcp-skills/shadcn/SKILL.md ``` **Step 2: Use the central executor.py** (from project root): ```bash # List available skills python .claude/skills/mcp-skills/executor.py --skills # List tools in a skill python .claude/skills/mcp-skills/executor.py --skill github --list # Get tool schema python .claude/skills/mcp-skills/executor.py --skill github --describe create_issue # Call a tool python .claude/skills/mcp-skills/executor.py --skill github --call '{"tool": "create_issue", "arguments": {...}}' ``` ## Context Efficiency | Scenario | Native MCP (all servers) | This Registry | Savings | |----------|--------------------------|---------------|---------| | Idle | 40-100k tokens | ~150 tokens | 99%+ | | Using 1 skill | 40-100k tokens | ~5k tokens | 90%+ | | After execution | 40-100k tokens | ~150 tokens | 99%+ | ## How It Works 1. **Registry loads first** - This file (~150 tokens) 2. **User requests a tool** - e.g., "create a GitHub PR" 3. **Sub-skill loads** - Only the relevant skill's SKILL.md (~4k tokens) 4. **Executor runs** - External process, 0 context tokens 5. **Result returned** - Context drops back to registry only ## Adding New Skills Use the `mcp-to-skill-converter` skill: ```bash cd .claude/skills/mcp-to-skill-converter python mcp_to_skill.py --name <server-name> # Outputs to .claude/skills/mcp-skills/<server-name>/ ``` ## Skill Structure The registry has a central executor with per-skill configs: ``` .claude/skills/mcp-skills/ ├── executor.py # Central executor for ALL skills ├── SKILL.md # This registry file ├── index.json # Skill metadata registry └── <skill-name>/ ├── SKILL.md # Tool documentation ├── mcp-config.json # Server config └── package.json # Dependencies ``` --- *This registry enables progressive disclosure of MCP servers as Claude Skills.*

Frequently asked questions