What is Simple Mcp Prompt Engineer

simple-mcp-prompt-engineer is a powerful prompt optimization server that utilizes the Model Context Protocol (MCP) to systematically enhance AI prompts through various stages of optimization, including analysis, rule application, structuring, verification, and refinement.

Use cases

Use cases include optimizing prompts for chatbots, enhancing AI-generated content, refining user queries for better search results, and improving overall AI communication effectiveness.

How to use

To use simple-mcp-prompt-engineer, set up a virtual environment, install the necessary dependencies, and run the server. You can integrate it with Claude Desktop by configuring the MCP server settings.

Key features

Key features include smart prompt analysis, rule-based optimization, structured output for clarity, iterative refinement based on user feedback, and tracking of optimization history across multiple versions.

Where to use

simple-mcp-prompt-engineer can be used in fields such as AI development, natural language processing, and any application requiring prompt engineering for improved AI interactions.

Simple MCP Prompt Engineer

This project implements a powerful prompt optimization server using the Model Context Protocol (MCP). It provides a systematic approach to improving AI prompts through multiple stages of optimization, including analysis, rules application, structuring, verification, and refinement.

Features

• 🔍 Smart Prompt Analysis: Identifies prompt types and opportunities for improvement
• 🔧 Rule-Based Optimization: Applies best practices for prompt engineering
• 📋 Structured Output: Improves organization and clarity of prompts
• 🔄 Iterative Refinement: Allows further improvements based on user feedback
• 📊 Optimization History: Tracks the evolution of prompts over multiple versions

Setup

# Create and activate virtual environment
uv venv
.venv\Scripts\activate     # Windows
source .venv/bin/activate  # Unix

# Install dependencies
uv pip install rich mcp-server

Project Structure

simple-mcp-prompt-engineer/
├── simple-mcp_prompt_engineer/
│   ├── server.py
│   └── __init__.py
├── README.md

Claude Desktop Integration

Add to your Claude Desktop configuration.

API

The server exposes four main tools:

1. optimize_prompt

Automatically optimizes a prompt based on best practices.

Parameters:

• prompt (str): The original prompt to optimize

Returns:

• Optimized prompt

2. refine_prompt

Refines the current prompt based on user feedback.

Parameters:

• feedback (str): User feedback for further refinement

Returns:

• Refined prompt

3. get_optimization_history

Get the full optimization history.

Returns:

• JSON string containing the optimization history

4. clear_optimization_history

Clear the optimization history.

Returns:

• Confirmation message

Optimization Process

The prompt optimization goes through the following stages:

1. Initial Analysis: Detecting prompt type and structure
2. Rules Application: Applying best practices for prompt engineering
3. Structuring: Organizing content into clear sections
4. Verification: Ensuring all important context is preserved
5. Refinement: Applying user feedback for further improvements
6. Final: Polished, optimized prompt ready for use

License

MIT License

Acknowledgments

This project is totally inspired by the Model Context Protocol repository and framework. Their pioneering work on creating standardized protocols for AI model interactions has made projects like this possible.

Author

Riccardo Fusco