meGPT - upload an author's content into an LLM

Name: meGPT - upload an author's content into an LLM
Author: adrianco

@adrianco

Repository

About meGPT - upload an author's content into an LLM

Code to process many kinds of content by an author into an MCP server

#megpt #content-processing #llm

Basic information

Config

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

{
  "mcpServers": {
    "meGPT": {
      "command": "python",
      "args": [
        "mcp_server.py",
        "--author",
        "virtual_adrianco"
      ]
    }
  }
}

Tools

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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.

FAQ from meGPT

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.

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.