🛠️ skills.sh MCP Server

An unofficial Model Context Protocol (MCP) server for the skills.sh ecosystem. This server empowers your AI agents (like Claude Code, Antigravity-cli, or Cursor) to autonomously search, evaluate, and install the most relevant skills directly from the skills.sh catalog.

📦 NPM Package: skills-mcp-server

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✨ Features

• Zero-Config & No Auth: Uses public endpoints—no Vercel tokens or API keys required.
• AI-Native & Self-Documenting: Natively embeds detailed workflow instructions via MCP Prompts and Resources so your LLM always knows exactly how to search effectively.
• 4 Powerful Tools:
  • search_skills: Semantic search through the catalog.
  • get_skill_details: Deep-dive analytics (installs, platforms, history).
  • get_popular_skills: Discover trending and hot skills.
  • get_install_command: Instantly generate npx installation commands.

🚀 Quick Start (Recommended)

For Claude Code

You can install this directly into Claude Code with a single command:

claude mcp add skills-sh -- npx -y skills-mcp-server

For Claude Desktop & Cursor

Add the following to your MCP client configuration (e.g., claude_desktop_config.json):

{
  "mcpServers": {
    "skills-sh": {
      "command": "npx",
      "args": [
        "-y",
        "skills-mcp-server"
      ]
    }
  }
}

Global Installation (Optional)

If you prefer not to use npx every time, you can install it globally:

npm install -g skills-mcp-server

Then use skills-mcp-server as your command instead of npx.

💻 Running from Source

If you prefer to run the server locally:

1. Clone this repository.
2. Install dependencies: npm install
3. Build the project: npm run build
4. Add the absolute path to your MCP client config:

{
  "mcpServers": {
    "skills-sh": {
      "command": "node",
      "args": [
        "/absolute/path/to/your/skills-mcp-server/build/index.js"
      ]
    }
  }
}

🧠 How the AI Uses This Server

This server is designed to be fully self-documenting for LLMs.

When your agent connects, it automatically gains access to:

1. Rich Tool Descriptions: Tools contain explicit instructions telling the LLM to generate diverse keywords, loop searches, and thoroughly vet results before recommending them.
2. MCP Resources: Exposes a skills-sh://agent-instructions resource. Advanced clients can automatically read this to understand the full step-by-step searching workflow.
3. MCP Prompts: Exposes a skills-search-workflow prompt. Users can invoke this manually in supported clients to force the LLM into a highly optimized "Skill Search Mode".

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Acknowledgements

Core API discovery and initial implementation credit goes to brandonqr/skillsh-mcp.