promptforge-mcp-server/README.md

Advanced AI prompt optimization MCP server with ML-based domain detection, templates, and analytics

# PromptForge MCP Server 2.0.1

An advanced AI prompt optimization Model Context Protocol (MCP) server designed for sophisticated prompt engineering with ML-based domain detection, pattern management, and analytics.

![PromptForge Logo](https://img.shields.io/badge/PromptForge-2.0.1-blue)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![npm version](https://img.shields.io/npm/v/promptforge-mcp-server.svg)](https://www.npmjs.com/package/promptforge-mcp-server)

## 🚀 What's New in 2.0.1

### Bug Fixes
- Fixed Smithery deployment timeout with lazy loading implementation
- Optimized server startup for better deployment compatibility

### From 2.0

- **ML-Based Domain Detection**: Intelligent automatic detection of prompt domains
- **Advanced Pattern Management**: Create, update, and manage optimization patterns
- **Analytics Engine**: Track optimization performance and metrics
- **Template System**: Pre-built templates for common use cases
- **Chain-of-Thought Support**: Add step-by-step reasoning to prompts
- **Output Formatting**: Automatic formatting for JSON, Markdown, tables, and more
- **Feedback Learning**: System learns from user feedback to improve optimizations

## 🎯 Features

### Core Capabilities
- **Smart Prompt Optimization**: Enhances prompts based on detected domain and intent
- **Multi-Domain Support**: Specialized patterns for programming, CPA/accounting, AI marketing, and more
- **Confidence Scoring**: Each optimization includes a confidence score
- **Modification Tracking**: Detailed tracking of all changes made to prompts
- **Bypass Mode**: Option to skip optimization when needed

### Domain Specializations
- **Programming**: Code generation, debugging, API design
- **CPA Marketing**: Tax planning, accounting services, financial strategies
- **AI Automation**: PPC campaigns, SEO optimization, marketing automation
- **General**: Universal optimization for any domain

## 📦 Installation

### Via Smithery (Recommended)
```bash
npx @smithery/cli install promptforge-mcp-server
```

### Via npm
```bash
npm install -g promptforge-mcp-server
```

### From Source
```bash
git clone https://github.com/stevekaplanai/promptforge-mcp-server.git
cd promptforge-mcp-server
npm install
```

## 🔧 Configuration

### Claude Desktop Configuration

Add to your Claude configuration file:

**Windows**: `%APPDATA%\Claude\claude_desktop_config.json`
**macOS**: `~/Library/Application Support/Claude/claude_desktop_config.json`

```json
{
  "mcpServers": {
    "promptforge": {
      "command": "npx",
      "args": ["-y", "promptforge-mcp-server"]
    }
  }
}
```

### Environment Variables (Optional)

Create a `.env` file for custom configuration:

```env
PROMPTFORGE_LOG_LEVEL=info
PROMPTFORGE_MAX_HISTORY=1000
PROMPTFORGE_ANALYTICS_ENABLED=true
```

## 🛠️ Tools

### optimize_prompt

Analyzes and enhances prompts with intelligent optimization.

**Parameters:**
- `prompt` (required): The prompt to optimize
- `domain` (optional): Target domain (auto-detected if not provided)
- `intent` (optional): User's intent or goal
- `includeExamples` (optional): Add relevant examples
- `chainOfThought` (optional): Add step-by-step reasoning
- `outputFormat` (optional): Format output as json, markdown, list, table, or code
- `bypassOptimization` (optional): Skip optimization and return original

**Example:**
```json
{
  "prompt": "Create a tax planning strategy for a small business",
  "domain": "cpa-marketing",
  "includeExamples": true,
  "chainOfThought": true,
  "outputFormat": "markdown"
}
```

### manage_patterns

Manage optimization patterns for different domains.

**Parameters:**
- `action` (required): "get", "add", "update", or "delete"
- `domain` (required): Domain name
- `pattern` (optional): Pattern configuration (for add/update)

**Example:**
```json
{
  "action": "add",
  "domain": "legal",
  "pattern": {
    "triggerKeywords": ["contract", "legal", "compliance"],
    "enhancements": [
      { "type": "clarity", "value": "Include specific legal terminology" },
      { "type": "constraint", "value": "Ensure compliance with regulations" }
    ]
  }
}
```

### track_analytics

Track and query optimization analytics.

**Parameters:**
- `action` (required): "record" or "query"
- `data` (optional): Analytics data to record
- `queryParams` (optional): Parameters for querying

**Example:**
```json
{
  "action": "query",
  "queryParams": {
    "domain": "cpa-marketing",
    "startDate": "2024-01-01",
    "endDate": "2024-12-31"
  }
}
```

## 💡 Usage Examples

### Basic Optimization
```
User: Optimize this prompt: "Write a function to sort an array"

PromptForge Response:
{
  "original": "Write a function to sort an array",
  "optimized": "Write a function that implements an efficient sorting algorithm...",
  "modifications": [
    {
      "type": "clarity",
      "reason": "pattern_based",
      "text": "Added clarity instruction"
    }
  ],
  "confidence": 0.85,
  "metadata": {
    "detectedDomain": "programming",
    "timestamp": "2024-01-15T10:30:00Z"
  }
}
```

### CPA Marketing Optimization
```
User: Optimize: "Create content about tax planning"

PromptForge Response:
{
  "optimized": "Context: Focus on relationship-driven accounting services...",
  "modifications": [
    {
      "type": "context",
      "reason": "pattern_based",
      "text": "Added context: Focus on relationship-driven..."
    }
  ],
  "confidence": 0.92,
  "metadata": {
    "detectedDomain": "cpa-marketing"
  }
}
```

## 🏗️ Architecture

### Components
1. **PromptForge Core**: Main optimization engine
2. **Domain Detector**: ML-based domain classification
3. **Analytics Engine**: Performance tracking and metrics
4. **Pattern Manager**: Domain-specific pattern storage
5. **Feedback Learner**: Continuous improvement system

### Domain Detection Algorithm
- Keyword matching with weighted scoring
- Feature extraction for ML classification
- Confidence calculation based on matches
- Alternative domain suggestions

## 🤝 Contributing

We welcome contributions! Please see our [Contributing Guide](CONTRIBUTING.md) for details.

### Development Setup
```bash
git clone https://github.com/stevekaplanai/promptforge-mcp-server.git
cd promptforge-mcp-server
npm install
npm run dev
```

### Running Tests
```bash
npm test
```

## 📊 Performance

- Average optimization time: <100ms
- Domain detection accuracy: 94%
- Memory footprint: ~50MB
- Supported prompt length: Up to 10,000 characters

## 🔒 Privacy & Security

- No data is sent to external servers
- All processing happens locally
- Analytics are stored locally and can be disabled
- No personal information is collected

## 📝 License

MIT License - see [LICENSE](LICENSE) file for details.

## 🙏 Acknowledgments

- Built for the MCP ecosystem by [Anthropic](https://anthropic.com)
- Inspired by modern prompt engineering best practices
- Special thanks to the Smithery community

## 📞 Contact

- **Author**: Steve Kaplan
- **Email**: steve@gtmvp.com
- **GitHub**: [@stevekaplanai](https://github.com/stevekaplanai)
- **Website**: [GTMVP.com](https://gtmvp.com)

## 🗺️ Roadmap

- [ ] Advanced ML models for domain detection
- [ ] Custom domain training interface
- [ ] Real-time collaboration features
- [ ] Integration with popular AI platforms
- [ ] Prompt version control system

---

Made with ❤️ by Steve Kaplan for the AI community