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What is Model Context Protocol (MCP) Server for Winston AI - the most accurate AI Detector.?
Winston AI MCP Server is designed to detect AI-generated content, plagiarism, and compare texts with ease. It offers features like AI text detection, image detection, plagiarism detection, and text comparison, supporting multiple languages and providing detailed reports.
Documentation
Winston AI MCP Server ⚡️
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
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
📦 Docker Support
Build and run with Docker:
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
Note: Replace your-winston-ai-api-key with your actual Winston AI API key. You can get one at https://dev.gowinston.ai.
📋 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!
Fork the repository
Create a feature branch (git checkout -b feature/amazing-feature)
Commit your changes (git commit -m 'Add amazing feature')
Push to the branch (git push origin feature/amazing-feature)
Open a Pull Request
📄 License
This project is licensed under the MIT License - see the LICENSE file for details.