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skills.sh MCP Server

skills.sh MCP Server

by ANeuronI

🛠️ skills.sh MCP Server

npm version

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


✨ 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.

Related MCP server: skills-master-mcp

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".


Acknowledgements

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

Available Tools

4 tools
get_install_commandB

Get the npx install command for a skill

Inputs: repo (required), owner (required).

get_skill_detailsA

Get detailed information about a specific skill. Use this tool ALWAYS after 'search_skills' to vet a skill before recommending it. It provides critical data like total installs, weekly installs, and supported platforms. Extract 'owner', 'repo', and 'skillId' from the search results table.

Inputs: repo (required), owner (required), skillId (required).

search_skillsA

Search for skills on skills.sh by query term.

CRITICAL WORKFLOW FOR AI AGENTS:

  1. Parse user intent and generate 3-5 diverse keywords (e.g., for "scrape websites", use "web scraping", "puppeteer", "crawler").

  2. Call this tool multiple times with different keywords if the first results are poor.

  3. DO NOT recommend a skill immediately. You MUST use 'get_skill_details' on top candidates to check their install counts and platforms first.

  4. Recommend the top 1-3 skills and provide the npx install command.

Inputs: query (required), limit.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    A3.8/5.0

    Scored across 4 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose: searching, getting details, retrieving install commands, and viewing popular skills. No overlap or ambiguity.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern in snake_case (e.g., get_install_command, search_skills), making them predictable and easy to understand.

    Tool Count5/5

    With 4 tools covering search, details, install commands, and popular skills, the set is well-scoped for a skill discovery and installation server—neither too sparse nor excessive.

    Completeness5/5

    The tools provide a complete workflow: search for skills, examine details, retrieve install commands, and browse popular skills. No obvious gaps for the stated purpose.

    Maintenance

    ActivityInactive
    ResponsivenessOutdated data

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