Advertise
MCP.so
Sign In
S

Skill Seekers MCP Server

@yusufkaraaslan

Repository

Basic information

Category

Memory & Knowledge

Transports

stdio

Author

yusufkaraaslan

Submitted by

yusyus

About Skill Seekers MCP Server

Transform 17 source types (docs, GitHub repos, PDFs, videos, Jupyter, Confluence, Notion, Slack/Discord) into AI-ready skills and RAG knowledge. 35 MCP tools for scraping, packaging, and exporting to vector databases. Supports 16+ LLM platforms.

#ai#rag#documentation#skills#mcp#knowledge-base#vector-database#preprocessing

Skill Seekers MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "skill-seekers": {
      "command": "python",
      "args": [
        "-m",
        "skill_seekers.mcp.server_fastmcp"
      ]
    }
  }
}

Skill Seekers MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Skill Seekers?

A CLI tool that transforms 17 source types (documentation websites, GitHub repos, PDFs, videos, Jupyter Notebooks, Word documents, EPUBs, OpenAPI specs, PowerPoint presentations, RSS feeds, man pages, Confluence wikis, Notion pages, Slack/Discord exports, and more) into structured knowledge assets for AI systems. It serves as a universal preprocessing layer between raw documentation and AI targets including Claude, Gemini, OpenAI, RAG pipelines (LangChain, LlamaIndex, Haystack), vector databases (Pinecone, ChromaDB, FAISS, Qdrant), and AI coding assistants (Cursor, Windsurf, Cline, Continue.dev).

How to use Skill Seekers?

Install via pip install skill-seekers. Then run skill-seekers create <source> (e.g., a URL, GitHub repository, or local path) to ingest content. Finally, export the resulting asset to any target platform using skill-seekers package output/<name> --target <platform> (e.g., claude, langchain, cursor). Use skill-seekers video --url ... for video sources.

Key features of Skill Seekers

  • Ingest from 17 source types: docs, GitHub, PDFs, videos, notebooks, wikis, and more
  • Export to 16 AI platforms: Claude, Gemini, OpenAI, LangChain, LlamaIndex, Haystack, multiple vector DBs, and AI coding assistants
  • AI-enhanced SKILL.md generation with 500+ line examples, patterns, and guides
  • Smart chunking that preserves code blocks and maintains context for RAG pipelines
  • Video extraction with transcripts, OCR, GPU auto-detection, and vision API fallback
  • Battle-tested: 2,540+ tests, 24+ preset configs, production-ready

Use cases of Skill Seekers

  • Build a production-grade AI Skill for Claude from a public API documentation site
  • Preprocess a GitHub

Comments

More Memory & Knowledge MCP servers

Snipara

alopez3006

MCP connector for Snipara, the Project Brain for AI coding agents

1

priostack

ideaswave

Open-source Python SDK & MCP interface for Priostack Agent Context Network (ACN). Zero-setup, autonomous memory orchestration for AI agents.

Azquo

Azquo Holdings Ltd

Exact, shared memory for AI agents: a hierarchical database where totals always add up, every write is attributed to the agent and person behind it, and any figure traces back to its source file. Agents create databases,

UmmahAPI

Yousuf Kazmi

Islamic source data for assistants: Quran, hadith, tafsir, duas, prayer times and qibla. Answers come from real sources with citations instead of recalled text, so verses and hadith are not hallucinated. 36,000+ hadiths

Groundwork

Rarefied-Earth

Groundwork: company memory for your AI tools. Docs public. Source closed. Public proof needs no account.

1
Advertise