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Skill Seekers

by skill-seekers

Converts documentation, code, files, media, and wikis into AI skills, RAG data, and vector-database-ready exports.

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Install Skill Seekers

Pick your client, then add it in one click or paste the config.

STDIOPython
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "skill-seekers-skill-seekers": {
      "command": "uvx",
      "args": [
        "skill-seekers"
      ]
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

We couldn’t confirm it starts correctly

We ran the install command but it didn't respond within our test window — this can mean a slow first-time install rather than a real problem.

uvx skill-seekers

No response to initialize.

This is an experimental automated check and can have false negatives — missing environment variables, a slow cold install, etc. It doesn’t necessarily mean something’s wrong. Last checked 28d ago.

Overview

skill-seekers/Skill_Seekers MCP server turns documentation, repositories, files, videos, notebooks, and knowledge-base exports into structured AI-ready assets. It supports source scraping, project scanning, skill packaging, AI enhancement, and exports for RAG pipelines, vector databases, coding assistants, and multiple AI platforms. Install the Python package with the MCP extra when you want to expose these workflows to compatible clients. Reach for it when you need to prepare varied technical or organizational sources for reusable agent context rather than query a single live data service.

Use cases

  • Create AI skills from product documentation
  • Scan a codebase for framework-specific context
  • Prepare source content for RAG pipelines
  • Package knowledge for coding assistants
  • Export documents for vector databases

Key features

  • Multi-source scraping and extraction
  • Codebase scanning
  • AI-assisted skill enhancement
  • AI skill packaging
  • RAG and vector database exports
  • MCP access to preparation workflows

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked Today

Recent health check succeeded.

28/29 checks healthy over the last 77d

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 7d ago via OSV.dev · skill-seekers (PyPI)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars15kStargazers on the source repository.
Last commit26d agoMost recent push to the default branch.
Install checkInconclusiveDidn't respond in our test window — often a slow first install.
Directory activity5 viewsConfig copies, upvotes, and views on AllMCPs.

How Skill Seekers works

What skill-seekers/Skill_Seekers MCP server does

It can collect information from documentation sites, GitHub repositories, local codebases, PDFs, Word documents, EPUB books, Jupyter notebooks, OpenAPI files, PowerPoint presentations, AsciiDoc, HTML, RSS or Atom feeds, and man pages. Optional support covers videos, Confluence, Notion, and Slack or Discord chat exports.

The resulting assets can be packaged as AI skills containing a SKILL.md and reference files, converted into chunked documents with metadata for retrieval workflows, or formatted for vector databases such as Pinecone, Chroma, Weaviate, FAISS, and Qdrant. Export targets include AI platforms and coding assistants such as Claude, Gemini, OpenAI, Cursor, Windsurf, and Cline.

How it works

The primary workflow is source creation followed by optional enhancement and packaging. A source can be supplied as a URL, repository identifier, local path, or source-specific command options. For example, the CLI can create a skill from a documentation URL, a GitHub repository, a local project, or a PDF. The output can then be packaged for a selected target.

For project analysis, the scan command examines manifests, README files, Docker or CI configuration, and sampled source imports. It produces configurations for detected frameworks and a codebase configuration that can be used in a later creation step. AI enhancement can use the default Claude agent, another named agent such as Kimi, or a custom agent command.

skill-seekers/Skill_Seekers MCP server adds MCP access to these scraping, scanning, packaging, enhancement, and export workflows. The README identifies the MCP installation extra for clients including Claude Code, Cursor, and other MCP-compatible environments.

Setup and configuration

Python 3.10 or newer and Git are listed as prerequisites. Install the base package for core scraping, repository handling, PDF processing, and packaging:

Terminal
pip install skill-seekers

Add the MCP extra to install MCP support:

Terminal
pip install 'skill-seekers[mcp]'

Optional extras cover all LLM integrations, video processing, notebooks, PowerPoint, Confluence, Notion, RSS, chat exports, AsciiDoc, or the complete feature set. Video transcript and metadata extraction uses the video extra; visual extraction and Whisper support use video-full, followed by the project’s setup command for GPU-aware dependencies.

Tools and capabilities

  • Create structured skills from web pages, repositories, local projects, and many file formats.
  • Process Confluence, Notion, and Slack or Discord exports when the corresponding extras are installed.
  • Scan codebases and generate framework-specific configuration files.
  • Enhance collected content with a selected or custom AI agent.
  • Package outputs for AI platforms and coding assistants.
  • Prepare chunked RAG content and vector-database-ready data.
  • Export material for LangChain, LlamaIndex, Haystack, Pinecone, Chroma, Weaviate, FAISS, and Qdrant workflows.

Limitations and notes

Feature availability depends on the relevant optional extra. Video workflows, for example, require separate video dependencies, while source systems such as Confluence, Notion, and chat exports have their own extras.

skill-seekers/Skill_Seekers MCP server is primarily a preparation and export layer. External services and AI agents may require their own credentials and configuration.

Read the full README View source on GitHub

Reviews

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Frequently Asked Questions about Skill Seekers

Install Python 3.10 or newer, then run `pip install 'skill-seekers[mcp]'`. Git is also listed as a prerequisite.

The documented sources include websites, GitHub repositories, local codebases, PDFs, Word and EPUB files, Jupyter notebooks, OpenAPI files, PowerPoint, AsciiDoc, HTML, RSS or Atom feeds, man pages, videos, Confluence, Notion, and Slack or Discord exports.

Yes. The documented targets include Pinecone, Chroma, Weaviate, FAISS, and Qdrant, along with RAG frameworks such as LangChain, LlamaIndex, and Haystack.

Yes.

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