Skill Seekers

by yusufkaraaslan

370 downloads

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About

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.

Details

Author: yusufkaraaslan
Downloads: 370
Categories: Knowledge Base, AI

- 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

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below

Plugin Name Skill Seekers

Command (node, npx, python, etc.)

Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

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

JSON

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

JSON

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

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

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

JSON

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

JSON

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

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

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

JSON

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

JSON

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

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

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

JSON

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

JSON

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

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

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

JSON

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

JSON

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

From the repository

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.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

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

McpServers

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

Skill Seekers

🧠 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!

🧠 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.

```bash

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Details

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Setting up with Highlight

From the repository

Claude Desktop / Cursor

McpServers

Skill Seekers

🧠 The Data Layer for AI Systems

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