Skill Seekers MCP Server

Local setup required. This server has to be cloned and prepared on your machine before you register it in Claude Code.
1

Set the server up locally

Run this once to clone and prepare the server before adding it to Claude Code.

Run in terminal
pip install skill-seekers
2

Register it in Claude Code

After the local setup is done, run this command to point Claude Code at the built server.

Run in terminal
claude mcp add skill-seekers -- node "<FULL_PATH_TO_SKILL_SEEKERS>/dist/index.js"

Replace <FULL_PATH_TO_SKILL_SEEKERS>/dist/index.js with the actual folder you prepared in step 1.

README.md

The data layer for AI systems.

Skill Seekers

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🧠 The data layer for AI systems. Skill Seekers turns documentation sites, GitHub repos, PDFs, videos, notebooks, wikis, and 10+ more source types into structured knowledge assets—ready to power AI Skills (Claude, Gemini, OpenAI), RAG pipelines (LangChain, LlamaIndex, Pinecone), and AI coding assistants (Cursor, Windsurf, Cline) in minutes, not hours.

🌐 Visit SkillSeekersWeb.com - Browse 24+ preset configs, share your configs, and access complete documentation!

📋 View Development Roadmap & Tasks - 134 tasks across 10 categories, pick any to contribute!

🌐 Ecosystem

Skill Seekers is a multi-repo project. Here's where everything lives:

Repository Description Links
Skill_Seekers Core CLI & MCP server (this repo) PyPI
skillseekersweb Website & documentation Live
skill-seekers-configs Community config repository
skill-seekers-action GitHub Action for CI/CD
skill-seekers-plugin Claude Code plugin
homebrew-skill-seekers Homebrew tap for macOS

Want to contribute? The website and configs repos are great starting points for new contributors!

🧠 The Data Layer for AI Systems

Skill Seekers is the universal preprocessing layer that sits between raw documentation and every AI system that consumes it. Whether you are building Claude skills, a LangChain RAG pipeline, or a Cursor .cursorrules file — the data preparation is identical. You do it once, and export to all targets.

# One command → structured knowledge asset
skill-seekers create https://docs.react.dev/
# or: skill-seekers create facebook/react
# or: skill-seekers create ./my-project

# Export to any AI system
skill-seekers package output/react --target claude      # → Claude AI Skill (ZIP)
skill-seekers package output/react --target langchain   # → LangChain Documents
skill-seekers package output/react --target llama-index # → LlamaIndex TextNodes
skill-seekers package output/react --target cursor      # → .cursorrules

What gets built

Output Target What it powers
Claude Skill (ZIP + YAML) --target claude Claude Code, Claude API
Gemini Skill (tar.

Tools (2)

create_skillTransform a source (URL, repo, or local path) into a structured knowledge asset.
package_skillPackage processed knowledge for specific AI targets like Claude, LangChain, or Cursor.

Configuration

claude_desktop_config.json
{"mcpServers": {"skill-seekers": {"command": "skill-seekers", "args": ["mcp"]}}}

Try it

Create a new AI skill from the React documentation at https://docs.react.dev/
Package the processed knowledge in output/react for use with Claude Code.
Convert my local project folder into a RAG-ready knowledge asset for LlamaIndex.
Generate a .cursorrules file from the documentation in my current repository.

Frequently Asked Questions

What are the key features of Skill Seekers?

Transforms 17 source types including documentation, GitHub repos, PDFs, and videos into structured knowledge.. Supports multiple AI targets including Claude Skills, LangChain, LlamaIndex, and Cursor.. Provides a universal preprocessing layer for RAG pipelines and AI coding assistants.. Integrated with Claude Code for seamless AI-ready skill generation..

What can I use Skill Seekers for?

Developers creating custom Claude Skills from existing project documentation.. Engineers building RAG pipelines for LangChain or LlamaIndex using local codebase knowledge.. Users generating .cursorrules files to improve AI coding assistant performance.. Teams centralizing documentation and wikis into structured assets for AI consumption..

How do I install Skill Seekers?

Install Skill Seekers by running: pip install skill-seekers

What MCP clients work with Skill Seekers?

Skill Seekers works with any MCP-compatible client including Claude Desktop, Claude Code, Cursor, and other editors with MCP support.

Turn this server into reusable context

Keep Skill Seekers docs, env vars, and workflow notes in Conare so your agent carries them across sessions.

Need the old visual installer? Open Conare IDE.
Open Conare