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Claude Skills

Organization
k-dense-ai

MCP server for searching and retrieving Claude Agent Skills using vector search

Publisherk-dense-ai
Repositoryclaude-skills-mcp
LanguagePython
Forks
64
Stars
384
Available tools
3
Transport typestdio
Categories
LicenseMIT
Links
  • Connect tools to AI workflows

    Claude Skills exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 3 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    384 stars and 64 forks from the linked repository.

Claude Skills MCP Server

This MCP server is no longer hosted or maintained. Agent Skills have been natively adopted by all major AI platforms — Cursor, Windsurf, Claude Code, Copilot, and others now support skills out of the box. There is no longer a need for an MCP bridge to deliver skills to your coding assistant. Thank you to everyone who used and contributed to this project!


Tests Python 3.12 License Code style: ruff PyPI version

Use Claude's powerful new Skills system with ANY AI model or coding assistant - including Cursor, Codex, GPT-5, Gemini, and more. This MCP server brings Anthropic's Agent Skills framework to the entire AI ecosystem through the Model Context Protocol.

A Model Context Protocol (MCP) server that provides intelligent search capabilities for discovering relevant Claude Agent Skills using vector embeddings and semantic similarity. This server implements the same progressive disclosure architecture that Anthropic describes in their Agent Skills engineering blog, making specialized skills available to any MCP-compatible AI application.

An open-source project by K-Dense AI - creators of autonomous AI scientists for scientific research.

This MCP server enables any MCP-compatible AI assistant to intelligently search and retrieve skills from our curated Claude Scientific Skills repository and other skill sources like the Official Claude Skills.

Demo

Claude Skills MCP in Action

Semantic search and progressive loading of Claude Agent Skills in Cursor

Highlights

  • Two-Package Architecture: Lightweight frontend (~15 MB) starts instantly; backend (~250 MB) downloads in background
  • No Cursor Timeout: Frontend responds in <5 seconds, solving the timeout issue
  • Semantic Search: Vector embeddings for intelligent skill discovery
  • Progressive Disclosure: Multi-level skill loading (metadata → full content → files)
  • Zero Configuration: Works out of the box with curated skills
  • Multi-Source: Load from GitHub repositories and local directories
  • Fast & Local: No API keys needed, with automatic GitHub caching
  • Configurable: Customize sources, models, and content limits

Quick Start

For Cursor Users

Add through the Cursor Directory, or add to your Cursor config (~/.cursor/mcp.json):

json
{
  "mcpServers": {
    "claude-skills": {
      "command": "uvx",
      "args": ["claude-skills-mcp"]
    }
  }
}

The frontend starts instantly and displays tools, automatically downloading and starting the backend in the background (~60-120s due to RAG dependencies, one-time). Subsequent uses are instant.

Using uvx (Standalone)

Run the server with default configuration:

bash
uvx claude-skills-mcp

This starts the lightweight frontend which auto-downloads the backend and loads ~90 skills from Anthropic's official skills repository and K-Dense AI's scientific skills collection.

With Custom Configuration

bash
# 1. Print the default configuration
uvx claude-skills-mcp --example-config > config.json

# 2. Edit config.json to your needs

# 3. Run with your custom configuration
uvx claude-skills-mcp --config config.json

Documentation

MCP Tools

The server provides three tools for working with Claude Agent Skills:

  1. find_helpful_skills - Semantic search for relevant skills based on task description
  2. read_skill_document - Retrieve specific files (scripts, data, references) from skills
  3. list_skills - View complete inventory of all loaded skills (for exploration/debugging)

See API Documentation for detailed parameters, examples, and best practices.

Architecture (v1.0.0)

The system uses a two-package architecture for optimal performance:

  • Frontend (claude-skills-mcp): Lightweight proxy (~15 MB)
    • Starts instantly (<5 seconds) ✅ No Cursor timeout!
    • Auto-downloads backend on first use
    • MCP server (stdio) for Cursor
  • Backend (claude-skills-mcp-backend): Heavy server (~250 MB)
    • Vector search with PyTorch & sentence-transformers
    • MCP server (streamable HTTP)
    • Auto-installed by frontend OR deployable standalone

Benefits:

  • ✅ Solves Cursor timeout issue (frontend starts instantly)
  • ✅ Same simple user experience (uvx claude-skills-mcp)
  • ✅ Backend downloads in background (doesn't block Cursor)
  • ✅ Can connect to remote hosted backend (no local install needed)

See Architecture Guide for detailed design and data flow.

Skill Sources

Load skills from GitHub repositories (direct skills or Claude Code plugins) or local directories.

By default, loads from:

Contributing

Contributions are welcome! To contribute:

  1. Report issues: Open an issue for bugs or feature requests
  2. Submit PRs: Fork, create a feature branch, ensure tests pass (uv run pytest tests/), then submit
  3. Code style: Run uvx ruff check src/ before committing
  4. Add tests: New features should include tests

Development

Version Management: This monorepo uses a centralized version system:

  • Edit the VERSION file at the repo root to bump the version
  • Run python3 scripts/sync-version.py to sync all references (or use --check to verify)
  • The scripts/build-all.sh script automatically syncs versions before building

For questions, email orion.li@k-dense.ai

Join Our Community! 🚀

We'd love to have you in our Slack community! Connect with other users, share tips and tricks, get help with your skills, and be the first to know about new features and updates.

👉 Join the K-Dense Community on Slack 👈

Whether you're building custom skills, integrating with different AI models, or just exploring the possibilities of Agent Skills, our community is here to support you!

Learn More

License

This project is licensed under the Apache License 2.0.

Copyright 2025 K-Dense AI (https://k-dense.ai)

Star History

Star History Chart

Installation

TypingMind
Prerequisites:

Node.js 18+

{
  "mcpServers": {
    "claude-skills": {
      "command": "uvx",
      "args": [
        "claude-skills-mcp"
      ]
    }
  }
}

Available Tools

  • find_helpful_skills

    Always call this tool FIRST whenever the question requires any domain-specific knowledge beyond common sense or simple recall. Use it at task start, regardless of the task and whether you are sure about the task, It performs semantic search over a curated library of proven skills and returns ranked candidates with step-by-step guidance and best practices. Do this before any searches, coding, or any other actions as this will inform you about the best approach to take.

  • read_skill_document

    Use after finding a relevant skill to retrieve specific documents (scripts, references, assets). Supports pattern matching (e.g., 'scripts/*.py') to fetch multiple files. Returns text content or URLs and never executes code. Prefer pulling only the files you need to complete the current step.

  • list_skills

    Returns the full inventory of loaded skills (names, descriptions, sources, document counts) for exploration or debugging. For task-driven work, prefer calling 'find_helpful_skills' first to locate the most relevant option before reading documents.

Use Claude Skills MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once Claude Skills is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add Claude Skills as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the Claude Skills MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "claude-skills": {
      "command": "npx",
      "args": [
        "-y",
        "claude-skills-mcp"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the Claude Skills MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the Claude Skills MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use Claude Skills to help me with this task?
Claude Skills
Sure. I read it.
Here is what I found using Claude Skills.

Frequently asked questions

What is the Claude Skills MCP server used for?

Claude Skills is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use Claude Skills MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use Claude Skills with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use Claude Skills MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With Claude Skills connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect Claude Skills MCP to TypingMind?

Claude Skills runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does Claude Skills MCP provide in TypingMind?

Claude Skills exposes 3 MCP tools that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use Claude Skills MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If Claude Skills requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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