SkillHub MCP
# ⚡ SkillHub MCP
**AI Resource Intelligence** — Find the right tool for any AI task.
Search, discover, and get recommendations from 20,000+ skills, tools, agents, rules, and MCP servers — all from your terminal or AI client.
[](https://www.npmjs.com/package/skillhub-mcp)
[](https://opensource.org/licenses/MIT)
## Quick Start
### 1. Setup (30 seconds)
```bash
npx skillhub-mcp setup
```
This auto-detects your installed AI clients (Codex, Claude, Cursor, Windsurf) and configures them automatically.
### 2. Restart your AI client
### 3. Done!
Your AI assistant can now discover and recommend tools. Try asking it:
> "What tools should I use to build a RAG pipeline with LangChain?"
---
## CLI Usage
SkillHub also works as a standalone CLI — no MCP client required.
### Recommend tools for a task
```bash
npx skillhub-mcp recommend "build a REST API with authentication"
```
Output:
```
#1 Express.js ✓ 9.2
Fast, unopinionated web framework for Node.js
tool · cross-platform · expressjs
→ matches technologies: express, node; relevant to: api, coding
#2 Passport.js 8.8
Authentication middleware for Node.js
tool · cross-platform · jaredhanson
→ matches technologies: node; relevant to: authentication
```
### Search resources
```bash
npx skillhub-mcp search "vector database"
```
### Get resource details
```bash
npx skillhub-mcp info "LangChain"
```
### Database statistics
```bash
npx skillhub-mcp stats
```
### JSON output
All data commands support `--json` for piping and scripting:
```bash
npx skillhub-mcp recommend "kubernetes" --json | jq '.results[0]'
npx skillhub-mcp stats --json
```
---
## MCP Tools
When connected to an AI client, SkillHub exposes these tools:
| Tool | Description |
|------|-------------|
| `recommend` | Analyze a task and recommend relevant resources |
| `search` | Search 20,000+ resources by keyword |
| `get_resource` | Get full details for a specific resource |
| `get_setup_guide` | Get install instructions for any resource |
| `analyze_stack` | Recommend tools based on your tech stack |
---
## Security & Trust
**This package is designed to be safe and auditable.**
- ✅ **Fully offline** — zero network requests, no HTTP calls, no telemetry
- ✅ **Zero runtime dependencies** — self-contained bundle, nothing from `node_modules`
- ✅ **No install scripts** — no `postinstall`, no code runs on `npm install`
- ✅ **No eval** — no `eval()`, `new Function()`, or dynamic code execution
- ✅ **No shell access** — no `exec()`, `spawn()`, or `child_process` usage
- ✅ **Filesystem access only in setup wizard** — writes MCP client configs when you explicitly run `setup`
See [SECURITY.md](SECURITY.md) for full details on runtime behavior and filesystem access.
---
## Diagnostics
```bash
npx skillhub-mcp doctor
```
Checks Node.js version, `npx` path resolution, database loading, and MCP client configuration status.
---
## Manual Client Setup
If the setup wizard doesn't work for your client, generate the config manually:
```bash
npx skillhub-mcp print-config codex # Codex (TOML)
npx skillhub-mcp print-config claude # Claude Desktop (JSON)
npx skillhub-mcp print-config cursor # Cursor (JSON)
npx skillhub-mcp print-config windsurf # Windsurf (JSON)
```
> **Important:** The setup wizard uses absolute paths for `npx` (e.g., `/opt/homebrew/bin/npx`). GUI applications often don't inherit your shell's PATH.
---
## Requirements
- Node.js 18+
- npm / npx
## License
MIT
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## Sponsors
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TDQS
Scored across 5 tools
Each tool has a clear, distinct purpose: analyze_stack for stack analysis, recommend for general recommendations, search for database queries, get_resource for details, and get_setup_guide for installation instructions. There is no overlap, and agents can easily distinguish them.
Most tools follow a verb_noun pattern (analyze_stack, get_resource, get_setup_guide), but recommend and search are single verbs. This is a minor inconsistency but still predictable and readable.
With 5 tools, the set is well-scoped for a resource discovery and recommendation server. Each tool serves a necessary function without redundancy or bloat.
The tools cover the core workflow: stack analysis, general recommendation, search, resource details, and setup guides. Minor gaps like user feedback or comparison features exist but do not hinder the primary purpose.