MCP Server

The REST API works great for HTTP clients. But AI agents speak MCP — the Model Context Protocol. The @skillkit/mcp package lets agents discover skills natively, without HTTP calls or curl commands.

Think of it as giving your agent a direct line to the entire skill catalog.

Setup

Claude Desktop

Add this to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "skillkit": {
      "command": "npx",
      "args": ["@skillkit/mcp"]
    }
  }
}

Restart Claude Desktop. Done.

Cursor

Add to .cursor/mcp.json in your project:

{
  "mcpServers": {
    "skillkit": {
      "command": "npx",
      "args": ["@skillkit/mcp"]
    }
  }
}

Any MCP client

The server uses stdio transport. Works with any MCP-compatible client:

npx @skillkit/mcp

What your agent can do

Once connected, your agent gets four tools:

Search skills

Ask your agent: "Find skills for React performance optimization"

Behind the scenes, it calls search_skills with your query and returns ranked results. You can filter by tags, category, or source repository.

> Search for authentication skills tagged with "security"

The agent searches across the full catalog, ranks results by relevance, and shows you the best matches.

Get a specific skill

Ask: "Get the pdf-processing skill from anthropics/skills"

The agent calls get_skill and returns the full skill details — description, tags, content, and references.

Get recommendations

Ask: "What skills would you recommend for my TypeScript React project?"

The agent calls recommend_skills with your stack context (languages, frameworks, libraries) and returns personalized suggestions ranked by relevance.

Browse categories

Ask: "What skill categories are available?"

The agent calls list_categories and returns all categories with counts, so you know what's out there.

Resources

The server also exposes two read-only resources:

• skills://trending — Top 20 skills by relevance score
• skills://categories — All categories with counts

Agents can read these without making a tool call.

How it works

1. On startup, the server loads all skills from the marketplace catalog
2. Your agent sends a natural language request
3. The MCP client translates it into a tool call
4. The RelevanceRanker scores and ranks results (same algorithm as the REST API)
5. Results come back as structured JSON through the MCP protocol

Same ranking, same data, same quality — just native to your agent instead of going through HTTP.