Skillhub MCP

Links

• PyPI: https://pypi.org/project/skillhub-mcp/
• PyPI v1.0.1: https://pypi.org/project/skillhub-mcp/1.0.1/
• Skills directory: http://skills.214140846.net/

mcp-name: io.github.214140846/skillhub-mcp

You already have Claude-style skills (SKILL.md), but in practice you often hit a wall:

• your client speaks MCP, not Claude Skills
• your team uses multiple agents (Cursor, Copilot, Codex, etc.), so skills are painful to reuse across tools
• you want a more flexible way to organize and ship skills (nested folders, zip packaging)

Skillhub MCP bridges that gap: it turns Claude-style skills into MCP tools, so any MCP client can call the same skills.

⚠️ Experimental. Skills may contain scripts/resources. Treat them as untrusted and run with sandboxes/containers when possible.

Is this an MCP server or an MCP client?

This project is an MCP server.

• Skillhub MCP (this repo): runs as a server process and exposes tools/resources to clients.
• MCP clients: editors/agents like Cursor, Claude Code, Codex, etc. They start or connect to MCP servers.

What You Get

• Cross-client reuse: install once, use from any MCP client
• Flexible packaging: nested directories, .zip and .skill archives
• Skill resources: expose scripts/datasets/examples as MCP resources (files the client can read)
• Resource fallback: a fetch_resource tool for clients without native MCP resource support
• Multiple transports: stdio (default), http, sse

Quick Start

Default skills root: ~/.skillhub-mcp

uvx (recommended)

{
  "skillhub-mcp": {
    "command": "uvx",
    "args": ["skillhub-mcp@latest"]
  }
}

Use a custom skills root:

{
  "skillhub-mcp": {
    "command": "uvx",
    "args": ["skillhub-mcp@latest", "/path/to/skills"]
  }
}

Install in Popular Editors (MCP Clients)

Below are minimal working examples for mainstream “vibe coding” editors.

Cursor

Cursor supports configuring MCP servers via mcp.json. Add the following to your global ~/.cursor/mcp.json or project .cursor/mcp.json, then restart Cursor.

{
  "mcpServers": {
    "skillhub-mcp": {
      "type": "stdio",
      "command": "uvx",
      "args": ["skillhub-mcp@latest", "/path/to/skills"]
    }
  }
}

Claude Code

Option A: configure via Claude Code CLI (recommended for quick setup):

claude mcp add --transport stdio skillhub-mcp -- uvx skillhub-mcp@latest /path/to/skills

Option B: project-scoped configuration via .mcp.json at your project root. You may need to explicitly allow project MCP servers in .claude/settings.json.

./.mcp.json

{
  "mcpServers": {
    "skillhub-mcp": {
      "type": "stdio",
      "command": "uvx",
      "args": ["skillhub-mcp@latest", "/path/to/skills"]
    }
  }
}

./.claude/settings.json (approve only this server)

{
  "enabledMcpjsonServers": ["skillhub-mcp"]
}

Codex (OpenAI)

Option A: use the Codex CLI to add a stdio MCP server:

codex mcp add skillhub-mcp -- uvx skillhub-mcp@latest /path/to/skills

Option B: edit ~/.codex/config.toml:

[mcp_servers.skillhub-mcp]
command = "uvx"
args = ["skillhub-mcp@latest", "/path/to/skills"]

Skill Format

Skillhub MCP discovers skills under the root directory (default ~/.skillhub-mcp). Each skill can be:

• a directory containing SKILL.md
• a .zip or .skill archive containing SKILL.md (at the archive root or inside a single top-level folder)

All other files become downloadable MCP resources for your agent to read. Note: Skillhub MCP does not execute scripts; the client decides whether/how to run them.

Example layout:

~/.skillhub-mcp/
├── summarize-docs/
│   ├── SKILL.md
│   ├── summarize.py
│   └── prompts/example.txt
├── translate.zip
├── analyzer.skill
└── web-search/
    └── SKILL.md

Archive rules:

translate.zip
├── SKILL.md
└── helpers/
    └── translate.js

data-cleaner.zip
└── data-cleaner/
    ├── SKILL.md
    └── clean.py

Directory Structure: Skillhub MCP vs Claude Code

Claude Code expects a flat skills directory (each immediate subdirectory is one skill). Skillhub MCP is more permissive:

• nested directories are discovered
• .zip / .skill packaged skills are supported

If you need Claude Code compatibility, keep the flat layout.

CLI Reference

skillhub-mcp [skills_root] [options]

Flag / Option	Description
positional skills_root	Optional skills directory (defaults to ~/.skillhub-mcp).
--transport {stdio,http,sse}	Transport (default stdio).
--host HOST	Bind address for HTTP/SSE transports.
--port PORT	Port for HTTP/SSE transports.
--path PATH	URL path for HTTP transport.
--list-skills	List discovered skills and exit.
--verbose	Emit debug logging.
--log	Mirror verbose logs to /tmp/skillhub-mcp.log.

Safety Notes

• Skills are not "just prompts": they can include scripts and arbitrary files.
• Skillhub MCP does not run scripts, but your client might. Prefer running in a sandbox/container.

Language

• English: README.md
• 中文: README.zh-CN.md

About the Author

I focus on AI SaaS going global, covering the full journey from idea validation and vibe coding to product development, infrastructure, SEO, backlinks, and growth experiments.

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