How do I use Prompt Auto-Optimizer MCP?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Prompt Auto-Optimizer MCP start optimizing a prompt for summarizing research papers" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

Prompt Auto-Optimizer MCP

AI-Powered Prompt Evolution - An MCP server that automatically optimizes your AI prompts using evolutionary algorithms.

🎯 Purpose

Automatically evolve and optimize AI prompts to improve performance, creativity, and reliability. Uses genetic algorithms to iteratively improve prompts based on real performance data.

Related MCP server: MCP Anthropic Server

🛠️ Installation

# Clone and install git clone https://github.com/your-org/prompt-auto-optimizer-mcp.git cd prompt-auto-optimizer-mcp npm install npm run build # Start the MCP server npm run mcp:start

⚙️ Configuration

Add to your Claude Code settings (.claude/settings.json):

{ "mcp": { "servers": { "prompt-optimizer": { "command": "npx", "args": ["prompt-auto-optimizer-mcp"], "cwd": "./path/to/prompt-auto-optimizer-mcp" } } } }

🔧 Available Tools

Core Optimization Tools

`gepa_start_evolution`

Start optimizing a prompt using evolutionary algorithms.

{ taskDescription: string; // What you want to optimize for seedPrompt?: string; // Starting prompt (optional) config?: { populationSize?: number; // How many variants to test (default: 20) generations?: number; // How many iterations (default: 10) mutationRate?: number; // How much to change prompts (default: 0.15) }; }

`gepa_evaluate_prompt`

Test how well a prompt performs on specific tasks.

{ promptId: string; // Which prompt to test taskIds: string[]; // What tasks to test it on rolloutCount?: number; // How many times to test (default: 5) }

`gepa_reflect`

Analyze why prompts fail and get improvement suggestions.

{ trajectoryIds: string[]; // Which test runs to analyze targetPromptId: string; // Which prompt needs improvement analysisDepth?: 'shallow' | 'deep'; // How detailed (default: 'deep') }

`gepa_get_pareto_frontier`

Get the best prompt candidates that balance multiple goals.

{ minPerformance?: number; // Minimum quality threshold limit?: number; // Max results to return (default: 10) }

`gepa_select_optimal`

Choose the best prompt for your specific use case.

{ taskContext?: string; // Describe your use case performanceWeight?: number; // How much to prioritize accuracy (default: 0.7) diversityWeight?: number; // How much to prioritize creativity (default: 0.3) }

`gepa_record_trajectory`

Log the results of prompt executions for analysis.

{ promptId: string; // Which prompt was used taskId: string; // What task was performed executionSteps: ExecutionStep[]; // What happened during execution result: { success: boolean; // Did it work? score: number; // How well did it work? }; }

Backup & Recovery Tools

gepa_create_backup - Save current optimization state
gepa_restore_backup - Restore from a previous backup
gepa_list_backups - Show available backups
gepa_recovery_status - Check system health
gepa_integrity_check - Verify data integrity

📝 Basic Usage

Start Evolution: Use gepa_start_evolution with your task description
Record Results: Use gepa_record_trajectory to log how prompts perform
Analyze Failures: Use gepa_reflect to understand what went wrong
Get Best Prompts: Use gepa_select_optimal to find the best candidates

🔧 Environment Variables

# Optional performance tuning GEPA_MAX_CONCURRENT_PROCESSES=3 # Parallel execution limit GEPA_DEFAULT_POPULATION_SIZE=20 # Default prompt variants GEPA_DEFAULT_GENERATIONS=10 # Default iterations

Built for better AI prompts • 📚 Docs • 🐛 Issues

Prompt Auto-Optimizer MCP

Prompt Auto-Optimizer MCP

🎯 Purpose

🛠️ Installation

⚙️ Configuration

🔧 Available Tools

Core Optimization Tools

`gepa_start_evolution`

`gepa_evaluate_prompt`

`gepa_reflect`

`gepa_get_pareto_frontier`

`gepa_select_optimal`

`gepa_record_trajectory`

Backup & Recovery Tools

📝 Basic Usage

🔧 Environment Variables

Resources

Tools

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