mcp-prompt-optimizer

Overview

MCP Prompt Optimizer is a professional-grade server that provides advanced prompt optimization tools with research-backed strategies. It delivers 15-74% performance improvements through various techniques including Tree of Thoughts, Constitutional AI, and Self-Refine. The server offers both basic optimization strategies (clarity, specificity, chain of thought) and advanced approaches with proven success rates. Additionally, it includes 11 production-ready templates across domains like business analysis, product management, and development.

Try asking AI

After installing, here are 5 things you can ask your AI assistant:

• analyze_prompt

  Analyzes prompt quality and identifies issues

  Try:Analyze this prompt: write a blog post about AI
• optimize_prompt

  Applies specific optimization strategies

  Try:Optimize this prompt using chain_of_thought: explain machine learning
• auto_optimize

  Automatically selects optimal strategy

  Try:Auto-optimize: help me debug this code
• get_prompt_template

  Returns basic templates

  Try:Get a template for code review
• advanced_optimize

  Applies research-backed strategies

  Try:Apply advanced optimization with tree_of_thoughts: design a microservices architecture
• get_domain_template

  Returns professional domain templates

  Try:Get domain template for code_review_checklist
• list_domain_templates

  Lists available templates by domain

  Try:List all domain templates

Comparable tools

Installation

# Clone the repository
git clone <repository-url>
cd mcp-prompt-optimizer

# Create virtual environment (recommended)
python3 -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
./install.sh
# Or install manually
pip install -r requirements.txt

{
  "mcpServers": {
    "prompt-optimizer": {
      "command": "python3",
      "args": ["/path/to/mcp-prompt-optimizer/prompt_optimizer.py"],
      "env": {}
    }
  }
}

FAQ

What prompt optimization strategies are available?

Both basic strategies (clarity, specificity, chain of thought, few-shot, structured output, role-based) and advanced strategies (Tree of Thoughts, Constitutional AI, Self-Refine, TEXTGRAD, Medprompt, etc.) are available.

How do I use specific optimization strategies?

Use commands like 'Optimize this prompt using chain_of_thought: explain machine learning' or 'Apply advanced optimization with tree_of_thoughts: solve this complex problem'.

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