Meta Prompt MCP Server

# Meta Prompt MCP This project is an implementation of the **Meta-Prompting** technique from the paper "[Meta-Prompting: Enhancing Language Models with Task-Agnostic Scaffolding](https://arxiv.org/abs/2401.12954)". At its core, this MCP transforms a standard Language Model (LM) into a dynamic, multi-agent system without the complex setup. It works by having the LM adopt two key roles: 1. **The Conductor**: A high-level project manager that analyzes a complex problem, breaks it down into smaller, logical subtasks, and delegates them. 2. **The Expert**: Specialized agents (e.g., "Python Programmer," "Code Reviewer," "Creative Writer") that are "consulted" by the Conductor to execute each subtask. The magic is that this entire collaborative workflow is simulated within a *single LM*. The Conductor and Experts are different modes of operation guided by a sophisticated system prompt, allowing the model to reason, act, and self-critique its way to a more robust and accurate solution. It's like having an automated team of AI specialists at your disposal, all powered by one model. <a href="https://glama.ai/mcp/servers/@tisu19021997/meta-prompt-mcp-server"> <img width="380" height="200" src="https://glama.ai/mcp/servers/@tisu19021997/meta-prompt-mcp-server/badge" alt="Meta Prompt Server MCP server" /> </a> ## Demo [](https://youtu.be/KATOgaj2upI) ## Getting Started ### 1. Clone the Repository First, clone this repository to your local machine. ```sh git clone https://github.com/tisu19021997/meta-prompt-mcp-server.git . cd meta-prompt-mcp-server ``` ### 2. Install `uv` This project uses `uv`, an extremely fast Python package manager from Astral. If you don't have it installed, you can do so with one of the following commands. **Note**: use `which uv` to know the path of your `uv` installation. **macOS / Linux:** ```sh curl -LsSf https://astral.sh/uv/install.sh | sh ``` **Windows (PowerShell):** ```powershell powershell -c "ir