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MCP Prompt Optimizer Server

Provides prompt optimization and domain templates through an MCP server with configurable local execution.

Installation

Add the following to your MCP client configuration file.

Configuration

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

You can run the MCP Prompt Optimizer as a dedicated server that enhances your prompts with research-backed optimization strategies and ready-to-use domain templates. It helps you get clearer, more actionable prompts, apply advanced reasoning patterns, and reuse production-ready templates across common domains.

How to use

You connect to the MCP Prompt Optimizer using an MCP client that supports standard server configurations. Start by choosing the optimization path that fits your task, then issue prompts to analyze quality, apply targeted optimization, or auto-select the best strategy for your needs. You can request domain templates to accelerate consistent work across projects, and you can combine multiple strategies for complex problems.

How to install

Prerequisites: you need Python installed on your system. You will also run a local setup to prepare the MCP server for use.

Quick setup

# 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

# Configure Claude Desktop
python3 setup_interactive.py

Manual configuration

Add to your Claude Desktop configuration file. This example uses the macOS path; adjust for Windows or Linux as needed.

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

Available tools

analyze_prompt

Analyzes prompt quality and identifies issues to improve clarity and effectiveness.

optimize_prompt

Applies specified optimization strategies to enhance prompt performance.

auto_optimize

Automatically selects the most suitable optimization strategy for a given task.

get_prompt_template

Returns basic templates to guide prompt construction.

advanced_optimize

Applies research-backed, advanced optimization strategies for complex tasks.

get_domain_template

Provides professional domain templates for structured outputs.

list_domain_templates

Lists all available domain templates by category.