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docs: add v1.12.0 runtime skill discovery documentation
- README: add Runtime Discovery, serve command, REST API, MCP, Python client sections with examples and comparison table update - Website Hero: update terminal animation with serve/API demo - Website Features: add REST & MCP APIs card, API Access comparison row - Website Commands: add Server tab with serve command options - Fumadocs: create rest-api.mdx, mcp-server.mdx, python-client.mdx - Fumadocs: update index (v1.12.0, architecture, discovery section), commands (serve command), and meta.json navigation
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README.md

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| **Context Sync** | Configure each agent separately | One config, synced everywhere |
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| **Session Memory** | Knowledge dies with each session | Persistent learning across agents |
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| **Skill Testing** | Hope it works | Test framework with assertions |
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| **Runtime Discovery** | No API access | REST API + MCP server + Python client |
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## 5-Minute Quick Start
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skillkit memory --global
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```
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### Runtime Skill Discovery
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Start a REST API server or MCP server for agent-native skill discovery:
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```bash
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# Start REST API server (port 3737)
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skillkit serve
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# Custom port and host
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skillkit serve --port 8080 --host localhost
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# Endpoints:
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# GET /search?q=react - Search skills
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# POST /search - Search with filters
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# GET /skills/owner/repo/id - Get specific skill
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# GET /trending - Top skills by relevance
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# GET /categories - Skill categories
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# GET /health - Server health check
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```
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**MCP Server** for Claude Desktop, Cursor, and any MCP client:
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```json
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{
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"mcpServers": {
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"skillkit": {
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"command": "npx",
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"args": ["@skillkit/mcp"]
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}
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}
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}
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```
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**Python Client:**
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```bash
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pip install skillkit-client
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```
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```python
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from skillkit import SkillKitClient
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async with SkillKitClient("http://localhost:3737") as client:
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results = await client.search("react performance", limit=5)
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skill = await client.get_skill("owner/repo", "skill-name")
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trending = await client.trending(limit=10)
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```
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### Skill Marketplace
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Browse and install from curated skill repositories:
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skillkit check # Check skill health and updates
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```
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### Runtime Discovery Server
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```bash
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skillkit serve # Start REST API on :3737
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skillkit serve --port 8080 # Custom port
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skillkit serve --host localhost # Bind to localhost
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skillkit serve --cors "http://localhost:3000" # Custom CORS
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skillkit serve --cache-ttl 3600000 # Cache TTL (1hr)
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```
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### Translation & Context
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```bash
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console.log(mode.capabilities); // Available MCP capabilities
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```
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### REST API (TypeScript)
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```typescript
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import { createApp, startServer } from '@skillkit/api';
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// Start with custom options
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await startServer({
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port: 3737,
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corsOrigin: '*',
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cacheTtlMs: 86_400_000,
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skills: [...],
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});
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```
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### Caching & Ranking
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```typescript
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import { MemoryCache, RelevanceRanker } from '@skillkit/core';
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// LRU cache with TTL
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const cache = new MemoryCache({ maxSize: 500, ttlMs: 86_400_000 });
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// Multi-signal relevance scoring (0-100)
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const ranker = new RelevanceRanker();
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const results = ranker.rank(skills, 'react performance');
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```
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## Skill Sources & Attribution
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SkillKit aggregates skills from trusted sources. We credit and link back to all original creators. Each source retains its original license.

docs/fumadocs/content/docs/commands.mdx

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# CLI Commands
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SkillKit provides 40+ commands organized into functional categories. Built on Clipanion v4 with interactive prompts via @clack/prompts.
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SkillKit provides 50+ commands organized into functional categories. Built on Clipanion v4 with interactive prompts via @clack/prompts.
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## Global Options
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skillkit cicd pre-commit # Generate pre-commit hooks
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```
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## Serve Command
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Start the SkillKit REST API server for runtime skill discovery.
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```bash
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skillkit serve [options]
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```
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| Option | Short | Default | Description |
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|--------|-------|---------|-------------|
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| `--port` | `-p` | `3737` | Port to listen on |
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| `--host` | `-H` | `0.0.0.0` | Host to bind to |
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| `--cors` || `*` | CORS allowed origin |
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| `--cache-ttl` || `86400000` | Cache TTL in milliseconds |
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### Examples
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```bash
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# Start with defaults
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skillkit serve
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# Custom port and host
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skillkit serve --port 8080 --host localhost
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# Restricted CORS
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skillkit serve --cors "http://localhost:3000"
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# Short cache TTL (1 hour)
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skillkit serve --cache-ttl 3600000
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```
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### Endpoints
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| Method | Path | Description |
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|--------|------|-------------|
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| GET | `/search?q=...` | Search skills |
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| POST | `/search` | Search with filters |
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| GET | `/skills/:owner/:repo/:id` | Get specific skill |
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| GET | `/trending?limit=20` | Trending skills |
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| GET | `/categories` | Skill categories |
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| GET | `/health` | Server health |
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| GET | `/cache/stats` | Cache statistics |
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## Utility Commands
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```bash

docs/fumadocs/content/docs/index.mdx

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SkillKit is a universal command-line interface (CLI) and programmatic toolkit for managing AI agent skills across **32 AI coding platforms**.
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**Current Version:** v1.8.0
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**Current Version:** v1.12.0
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## The Problem
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| **Workflow Orchestration** | Compose skills into multi-step automated workflows |
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| **Skill Testing** | Built-in test framework with assertions |
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| **CI/CD Integration** | GitHub Actions, GitLab CI, and pre-commit hooks |
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| **REST API Server** | Runtime skill discovery via HTTP on port 3737 |
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| **MCP Server** | Agent-native discovery for Claude Desktop, Cursor |
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| **Python Client** | Async Python SDK for the REST API |
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| **TypeScript API** | Full programmatic access to all features |
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| **Interactive TUI** | Beautiful terminal interface with real-time updates |
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[Learn more →](/docs/messaging)
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### Runtime Skill Discovery
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Start a REST API or MCP server for runtime skill discovery by agents and applications.
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```bash
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skillkit serve # REST API on :3737
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```
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```json
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{
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"mcpServers": {
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"skillkit": { "command": "npx", "args": ["@skillkit/mcp"] }
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}
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}
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```
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[REST API →](/docs/rest-api) · [MCP Server →](/docs/mcp-server) · [Python Client →](/docs/python-client)
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## Architecture
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| Tier | Components |
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|------|------------|
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| **User Interfaces** | CLI (Clipanion v4), TUI (OpenTUI/React), Documentation |
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| **User Interfaces** | CLI (Clipanion v4), TUI (OpenTUI/Solid.js), Documentation |
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| **APIs** | @skillkit/api (REST/Hono), @skillkit/mcp (MCP/stdio) |
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| **Business Logic** | @skillkit/core, @skillkit/agents (32 adapters) |
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| **Data Layer** | @skillkit/memory (CozoDB), @skillkit/mesh (WebSocket/UDP) |
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| **External Systems** | GitHub/GitLab, Marketplace (15,000+ skills) |
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3. [Commands](/docs/commands) - Full CLI reference
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4. [Skills](/docs/skills) - Skill format and lifecycle
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5. [API Reference](/docs/api-reference) - Programmatic access
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6. [REST API](/docs/rest-api) - Runtime discovery server
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7. [MCP Server](/docs/mcp-server) - Agent-native discovery
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8. [Python Client](/docs/python-client) - Python SDK
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## Use Cases
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---
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title: MCP Server
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description: Agent-native skill discovery via Model Context Protocol
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---
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# MCP Server
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The `@skillkit/mcp` package provides a Model Context Protocol (MCP) server for agent-native skill discovery. It works with Claude Desktop, Cursor, and any MCP-compatible client.
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## Setup
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### Claude Desktop
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Add to your Claude Desktop configuration (`~/Library/Application Support/Claude/claude_desktop_config.json`):
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```json
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{
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"mcpServers": {
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"skillkit": {
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"command": "npx",
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"args": ["@skillkit/mcp"]
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}
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}
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}
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```
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### Cursor
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Add to `.cursor/mcp.json`:
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```json
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{
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"mcpServers": {
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"skillkit": {
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"command": "npx",
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"args": ["@skillkit/mcp"]
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}
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}
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}
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```
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### Any MCP Client
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The server uses stdio transport. Run directly:
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```bash
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npx @skillkit/mcp
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```
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## Tools
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The MCP server exposes 4 tools:
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### search_skills
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Search for skills by keyword, tag, or description.
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| Parameter | Type | Required | Description |
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|-----------|------|----------|-------------|
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| `query` | string | Yes | Search query |
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| `limit` | number | No | Max results (1-50, default 10) |
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| `include_content` | boolean | No | Include full content |
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| `include_references` | boolean | No | Include references |
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| `filters.tags` | string[] | No | Filter by tags |
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| `filters.category` | string | No | Filter by category |
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| `filters.source` | string | No | Filter by source repo |
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**Example prompt:** "Search for React performance optimization skills"
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### get_skill
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Get details of a specific skill.
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| Parameter | Type | Required | Description |
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|-----------|------|----------|-------------|
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| `source` | string | Yes | Skill source (e.g., `owner/repo`) |
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| `skill_id` | string | Yes | Skill name |
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| `include_references` | boolean | No | Include references |
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**Example prompt:** "Get the pdf-processing skill from anthropics/skills"
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Get skill recommendations based on your tech stack and current task.
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| Parameter | Type | Required | Description |
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| `languages` | string[] | No | Programming languages |
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| `frameworks` | string[] | No | Frameworks used |
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| `libraries` | string[] | No | Libraries used |
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| `task` | string | No | Current task description |
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| `limit` | number | No | Max results (1-20, default 5) |
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**Example prompt:** "Recommend skills for a TypeScript React project using Next.js"
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### list_categories
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List all skill categories with their counts.
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**Example prompt:** "List all available skill categories"
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## Resources
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The MCP server exposes 2 resources:
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| URI | Description |
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| `skills://trending` | Top 20 trending skills by relevance score |
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| `skills://categories` | All skill categories with counts |
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## How It Works
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1. On startup, the server loads the skill catalog from `marketplace/skills.json`
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2. Skills are indexed and available for search via the 4 tools
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3. The `RelevanceRanker` from `@skillkit/core` scores results using multi-signal ranking
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4. Results are returned as structured JSON via the MCP protocol
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## Integration with AI Agents
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Once configured, your AI agent can natively discover and recommend skills:
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> "Search for skills related to authentication and security"
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The agent will call `search_skills` and return ranked results with descriptions and sources.
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> "What skills would you recommend for my React + TypeScript project?"
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The agent will call `recommend_skills` with your stack context and return personalized recommendations.

docs/fumadocs/content/docs/meta.json

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"commands",
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"configuration",
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"api-reference",
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"rest-api",
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"mcp-server",
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"python-client",
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"cicd",
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"teams",
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"custom-agents",

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