winston-ai-mcp-server

Winston AI MCP Server

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README
Winston AI MCP Server ⚡️

npm version License: MIT Node.js CI TypeScript

Model Context Protocol (MCP) Server for Winston AI - the most accurate AI Detector. Detect AI-generated content, plagiarism, and compare texts with ease.

✨ Features
🔍 AI Text Detection
  • Human vs AI Classification: Determine if text was written by a human or AI
  • Confidence Scoring: Get percentage-based confidence scores
  • Sentence-level Analysis: Identify the most AI-like sentences in your text
  • Multi-language Support: Works with text in various languages
  • Credit cost: 1 credit per word
🖼️ AI Image Detection
  • Image Analysis: Detect AI-generated images using advanced ML models
  • Metadata Verification: Analyze image metadata and EXIF data
  • Watermark Detection: Identify AI watermarks and their issuers
  • Multiple Formats: Supports JPG, JPEG, PNG, and WEBP formats
  • Credit cost: 300 credits per image
📝 Plagiarism Detection
  • Internet-wide Scanning: Check against billions of web pages
  • Source Identification: Find and list original sources
  • Detailed Reports: Get comprehensive plagiarism analysis
  • Academic & Professional Use: Perfect for content verification
  • Credit cost: 2 credits per word
🔄 Text Comparison
  • Similarity Analysis: Compare two texts for similarities
  • Word-level Matching: Detailed breakdown of matching content
  • Percentage Scoring: Get precise similarity percentages
  • Bidirectional Analysis: Compare both directions
  • Credit cost: 1/2 credit per total words found in both texts
🚀 Quick Start
Prerequisites
🛠️ Development
Running with npx 🔋
env WINSTONAI_API_KEY=your-api-key npx -y winston-ai-mcp
Building from Source
# Clone the repository
git clone https://github.com/gowinston-ai/winston-ai-mcp-server.git
cd winston-ai-mcp-server

# Install dependencies
npm install

# Build the project and start the server
npm run mcp-start
Environment Setup

Create a .env file in your project root:

WINSTONAI_API_KEY=your_actual_api_key_here
📦 Docker Support

Build and run with Docker:

# Build the image
docker build -t winston-ai-mcp .

# Run the container
docker run -e WINSTONAI_API_KEY=your_api_key winston-ai-mcp
📋 Available Scripts
  • npm run build - Compile TypeScript to JavaScript
  • npm start - Start the MCP server
  • npm run mcp-start - Compile TypeScript to JavaScript and Start the MCP server
  • npm run lint - Run ESLint for code quality
  • npm run format - Format code with Prettier
🔧 Configuration
For Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "winston-ai-mcp": {
      "command": "npx",
      "args": ["-y", "winston-ai-mcp"],
      "env": {
        "WINSTONAI_API_KEY": "your-api-key"
      }
    }
  }
}
For Cursor IDE

Add to your Cursor configuration:

{
  "mcpServers": {
    "winston-ai-mcp": {
      "command": "npx",
      "args": ["-y", "winston-ai-mcp"],
      "env": {
        "WINSTONAI_API_KEY": "your-api-key"
      }
    }
  }
}
📋 API Reference
AI Text Detection
{
  "text": "Your text to analyze (600+ characters recommended)",
  "file": "(optional) A file to scan. If you supply a file, the API will scan the content of the file. The file must be in plain .pdf, .doc or .docx format.",
  "website": "(optional) A website URL to scan. If you supply a website, the API will fetch the content of the website and scan it. The website must be publicly accessible."
}
AI Image Detection
{
  "url": "https://example.com/image.jpg"
}
Plagiarism Detection
{
  "text": "Text to check for plagiarism",
  "language": "en", // optional, default: "en"
  "country": "us"   // optional, default: "us"
}
Text Comparison
{
  "first_text": "First text to compare",
  "second_text": "Second text to compare"
}
🤝 Contributing

We welcome contributions!

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request
📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🔗 Links
⭐ Support

If you find this project helpful, please give it a star on GitHub!


Made with ❤️ by the Winston AI Team

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