# K-Dense-AI/claude-skills-mcp [Health: Active]

**Category:** 🔗 Aggregators  
**Repository:** https://github.com/K-Dense-AI/claude-skills-mcp  
**GitHub Stars:** 403  
**npm Downloads (last month):** 786  
**Views:** 4  
**Installs:** 0  
**Upvotes:** 0  
**Directory Page:** https://allmcps.com/mcp/k-dense-ai-claude-skills-mcp

## Description
Intelligent search capabilities to let every model and client use Claude Agent Skills like native.

## Claude Desktop Quick Installation
Install path detected from listing signals. Uses `uvx` (confidence: high):

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

## Documentation

## What K-Dense-AI/claude-skills-mcp MCP server does

K-Dense-AI/claude-skills-mcp MCP server makes Claude Agent Skills available to MCP-compatible AI applications. It indexes skill metadata and content, then uses vector embeddings and semantic similarity to find skills related to a task description. The project is intended for assistants and coding tools that need to discover relevant skills without relying on a platform-specific native skills implementation.

Default content comes from Anthropic's official skills repository, K-Dense's Scientific Agent Skills collection, and `~/.claude/skills` when that local directory exists. Additional GitHub repositories and local directories can be configured as skill sources.

## How it works

The distribution separates the MCP entry point from the heavier search implementation. The frontend is a small stdio package designed to start quickly, while the backend contains the vector-search stack based on PyTorch and sentence-transformers. On the first run, the frontend downloads and starts the backend in the background; later starts can reuse the downloaded components.

Search follows a progressive disclosure model. An assistant can first identify relevant skill metadata, load the complete skill content when needed, and then request individual files such as scripts, data, or reference material. The server also checks configured sources hourly and re-indexes them when changes are detected. GitHub content uses automatic caching, and the README states that no API keys are required.

## Setup and configuration

The final release, version 1.1.0, remains available from PyPI, and the project supports Python 3.12 and 3.13. A direct standalone launch uses `uvx claude-skills-mcp`. Cursor can run the same package through an MCP configuration with `uvx` as the command and `claude-skills-mcp` as its argument.

To customize the source repositories, local paths, embedding model, or content limits, generate an example configuration with `uvx claude-skills-mcp --example-config`, edit the resulting JSON, and start the server with `--config config.json`. The default setup loads more than 160 skills from the stated official and K-Dense collections, according to the README.

## Tools and capabilities

The MCP interface exposes three tools:

- `find_helpful_skills` searches for skills using a task description and semantic similarity.
- `read_skill_document` retrieves a selected file from a skill, including scripts, data, or references.
- `list_skills` returns the inventory of loaded skills for exploration or debugging.

The K-Dense-AI/claude-skills-mcp MCP server can therefore support both targeted discovery and inspection of the files behind a selected skill. Its source configuration is suitable for combining public GitHub skill repositories with directories maintained locally.

## Limitations and notes

K-Dense-AI/claude-skills-mcp MCP server is no longer hosted or maintained. The repository identifies version 1.1.0 as the final release and says that major AI platforms now support Agent Skills natively. New issues and pull requests may not be reviewed, so teams extending it should consider forking the repository.

The first backend download is comparatively large and may take roughly 60–120 seconds because of the retrieval dependencies. The frontend is designed to avoid client startup timeouts, but that initial setup still requires the backend components to be downloaded. The project is licensed under Apache License 2.0.

_Full upstream README: https://allmcps.com/mcp/k-dense-ai-claude-skills-mcp/readme_