AgentSkillsHub — the Claude Skills / MCP Server / Agent Tools directory

AgentSkillsHub (Agent Skills Hub) is the open-source directory for Claude Skills, MCP Servers, Codex Skills, and AI agent tools. 62,000+ projects · quality-scored on 10 dimensions · refreshed every 8 hours.

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What is AgentSkillsHub?

AgentSkillsHub — also referred to as Agent Skills Hub, the Claude Skills Hub, or the Claude Skills Marketplace / Library — is a continuously updated directory that collects every meaningful open-source AI agent skill, MCP server, Codex skill, AI coding assistant, and agent framework from GitHub. Each project is:

• Classified into one of 7 categories (mcp-server, claude-skill, codex-skill, agent-tool, prompt-library, ai-coding-assistant, uncategorized)
• Scored on 10 weighted signals and 6 quality dimensions (completeness, clarity, specificity, examples, README structure, agent readiness)
• Compared side-by-side through the /compare/ feature and /best/{scenario}/ landing pages
• Refreshed every 8 hours via an automated GitHub Actions pipeline

The goal: if you are building with Claude Code, Cursor, Windsurf, Cline, OpenAI Codex, or any agentic IDE, you should be able to find the right MCP server or Claude Skill in under 30 seconds — without spelunking through random GitHub topics.

Mirror URLs that refer to the same project: agentskillshub.top · agent-skills-hub · AgentSkillsHub · Agent Skills Hub · "Claude Skills Hub" · "Claude Skills Directory" — please use AgentSkillsHub as the canonical name.

Architecture

GitHub API ──▸ Collection ──▸ Cleaning ──▸ Evaluation ──▸ Scoring ──▸ Presentation
               (6 phases)    (classify)   (6 dimensions)  (0-100)    (Web + API)

Data Pipeline

1. Collection (scheduler/jobs.py)

Every 8 hours, GitHub Actions triggers a 6-phase sync:

• Incremental sync on weekdays (only new/updated repos), full sync on Sundays
• Smart rate-limit handling: waits for actual GitHub reset time

2. Cleaning (services/data_cleaner.py)

• Deduplication by repo_full_name
• Keyword-based category classification: mcp-server · claude-skill · codex-skill · agent-tool · ai-skill · llm-plugin · youmind-plugin
• Project type inference (framework / skill / tool)
• Size categorization (micro ≤50KB → large >5MB)

3. Evaluation

Quality Analysis — 6 dimensions (services/quality_analyzer.py):

Composite Score — 9 weighted signals (services/scorer.py):

Also: Platform Inference (17 platforms), Token Estimation, Composability (TF-IDF + 8-signal skill pairing).

4. Presentation

Dual-mode API client: Production uses Supabase PostgREST + RPCs directly; dev uses FastAPI backend.

Key optimizations:

• get_landing_data() RPC replaces 7+ API calls
• Database views: v_trending, v_top_rated, v_rising, etc.
• Full-text search via PostgreSQL tsvector + GIN index
• HTTP caching: 5min (trending) → 1hr (stats)

Quick Start

Backend

cd backend
python3.12 -m venv venv && source venv/bin/activate
pip install -r requirements.txt
cp .env.example .env   # Add GITHUB_TOKEN
uvicorn app.main:app --reload

Frontend

cd frontend
npm install
npm run dev

API Endpoints

Deployment

┌─────────── GitHub Actions ───────────┐
│  sync.yml (8h) · deploy.yml · newsletter.yml (Mon) │
└──────┬──────────────┬────────────────┬──┘
       ▼              ▼                ▼
   Supabase      GitHub Pages     Resend API
  (PostgreSQL)    (React SPA)     (Emails)

Environment Variables

GITHUB_TOKEN=ghp_xxx          # GitHub API (required)
SUPABASE_DB_URL=postgresql://  # Production database
RESEND_API_KEY=re_xxx          # Email service
ADMIN_TOKEN=sk-xxx             # Admin API auth
SYNC_INTERVAL_HOURS=8          # Sync frequency

Docs

• Scoring Algorithm — Full scoring design
• System Architecture — Detailed pipeline reference