What content types does meGPT support?
It supports YouTube videos, podcasts, books (PDFs), stories, blog archives (Medium, Blogger), Twitter archives, presentation slides, and InfoQ videos.
meGPT - upload an author's content into an LLM MCP Server
@adrianco
Basic information
About meGPT - upload an author's content into an LLM MCP Server
Code to process many kinds of content by an author into an MCP server
meGPT - upload an author's content into an LLM MCP Server config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"meGPT": {
"command": "python",
"args": [
"mcp_server.py",
"--author",
"virtual_adrianco"
]
}
}
}meGPT - upload an author's content into an LLM MCP Server tools
Tool list not available yet
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We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Overview
What is meGPT?
meGPT is a repository and MCP (Model Context Protocol) server that organizes an author's public content—including books, blogs, podcasts, videos, and social media archives—into a searchable knowledge base for AI applications. It enables the creation of an LLM persona that can answer questions and generate summaries in the author's voice.
How to use meGPT?
Clone the repository, set up a Python virtual environment, and install dependencies. Run python build.py <author> to process content, then start the MCP server with python mcp_server.py --author <author> for STDIO mode or --transport streamable-http --port 8080 for HTTP.
Key features of meGPT
- Supports books, blogs, Twitter archives, podcasts, and videos.
- Includes an MCP server with semantic search and filtering.
- Automatically detects and processes YouTube videos, playlists, and channels.
- Handles Medium and Blogger archive extraction.
- Generates MCP resources for any author directory.
- Supports STDIO, HTTP, and SSE transports.
Use cases of meGPT
- Building a chatbot that answers questions as if it were the author.
- Summarizing an author’s opinions from decades of content.
- Creating a searchable knowledge base for researchers or fans.
- Training a RAG-based LLM persona from published work.
Frequently asked questions
How can I contribute my own content?
Clone the repo and add your own directory under `authors/`. If you want to contribute freely, submit a pull request.
What are the system dependencies?
The server requires Python 3 and packages listed in `requirements.txt`. Setup uses a virtual environment.
What license is the content under?
All content in this repo is Creative Commons Attribution-ShareAlike. Permission is explicitly granted for use as a training set for the meGPT concept.
What transport protocols does the MCP server support?
The server supports STDIO, HTTP, and SSE transport modes, selectable via the `--transport` flag.
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