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MCP server that exposes Claude-style skills to any MCP client.
MCP server that exposes Claude-style skills to any MCP client.
Valid MCP server (0 strong, 3 medium validity signals). 5 known CVEs in dependencies (1 critical, 3 high severity) Package registry verified. Imported from the Official MCP Registry.
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Add this to your MCP configuration file:
{
"mcpServers": {
"mcp-server": {
"args": [
"skillhub-mcp"
],
"command": "uvx"
}
}
}From the project's GitHub README.
mcp-name: io.github.214140846/skillhub-mcp
You already have Claude-style skills (SKILL.md), but in practice you often hit a wall:
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.
This project is an MCP server.
.zip and .skill archivesfetch_resource tool for clients without native MCP resource supportstdio (default), http, sseDefault skills root: ~/.skillhub-mcp
{
"skillhub-mcp": {
"command": "uvx",
"args": ["skillhub-mcp@latest"]
}
}
Use a custom skills root:
{
"skillhub-mcp": {
"command": "uvx",
"args": ["skillhub-mcp@latest", "/path/to/skills"]
}
}
Below are minimal working examples for mainstream “vibe coding” editors.
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"]
}
}
}
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"]
}
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"]
Skillhub MCP discovers skills under the root directory (default ~/.skillhub-mcp).
Each skill can be:
SKILL.md.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
Claude Code expects a flat skills directory (each immediate subdirectory is one skill). Skillhub MCP is more permissive:
.zip / .skill packaged skills are supportedIf you need Claude Code compatibility, keep the flat layout.
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. |
README.mdREADME.zh-CN.mdI 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.
Everything shared here comes from real projects, real traffic, and real revenue attempts.
Feishu Knowledge Base:
Thor’s AI Going-Global Content Planning
A structured knowledge base documenting hands-on experience in AI product overseas expansion, including demand discovery, execution strategies, and common pitfalls.
Blog:
Long-form notes and case studies on building, launching, and iterating AI products in public.
Open-source Project (High Star):
Smart Campus System
Social:
Sharing real-time thoughts on indie hacking, AI tools, and product growth.
Product:
AI Video Generation Platform:
An online platform for AI-powered video generation, focused on practical use cases and real user workflows.
AI Video & Image Generation:
Model pages:
A curated collection of AI video and image generation tools, experiments, and capability tracking.
AI Video & Image Collection:
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