Image Recognition MCP

Image Recognition MCP Server

A Model Context Protocol (MCP) server that provides AI-powered image recognition and description capabilities using OpenAI's vision models.

Overview

This MCP server enables AI assistants to analyze and describe images through a simple URL-based interface. It leverages OpenAI's powerful vision models to provide detailed descriptions of images, making it easy to integrate image analysis capabilities into your AI workflows.

Features

• Image Analysis: Analyze images from URLs and get detailed descriptions
• OpenAI Integration: Uses OpenAI's latest vision models for accurate image recognition
• MCP Protocol: Fully compatible with the Model Context Protocol standard
• TypeScript: Built with TypeScript for type safety and better development experience
• Simple API: Easy-to-use interface for image description requests

Installation

Prerequisites

• Node.js 18+
• npm or yarn
• OpenAI API key

MCP Client Configuration

To use this server with an MCP client, add the following configuration:

{

"mcpServers": { "image-recognition": { "command": "npx", "args": ["-y", "@mcp-s/image-recognition-mcp"], "env": { "OPENAI_API_KEY": "your-actual-openai-api-key-here" } } } }

⚠️ IMPORTANT: The env section with your OpenAI API key is required - this is the only way the MCP server can function.

Usage

Available Tools

describe-image

Analyzes an image from a URL and provides a detailed description.

Parameters:

• imageUrl (string): The URL of the image to analyze

Example:

{

"tool": "describe-image", "arguments": { "imageUrl": "https://example.com/image.jpg" } }

Response:

{

"content": [ { "type": "text", "text": "The image shows a beautiful sunset over a mountain landscape with vibrant orange and pink colors in the sky..." } ] }

Integration with AI Assistants

This MCP server can be integrated with various AI assistants that support the MCP protocol, such as:

• Claude Desktop
• Other MCP-compatible AI systems

Development

Project Structure

image-recognition-mcp/

├── src/ │ └── index.ts # Main server implementation ├── dist/ # Compiled JavaScript output ├── package.json # Project dependencies and scripts ├── tsconfig.json # TypeScript configuration └── README.md # This file

Error Handling

The server includes robust error handling for:

• Invalid image URLs
• Network connectivity issues
• OpenAI API errors
• Invalid input parameters

Troubleshooting

Common Issues

Server fails to start or doesn't work:

• ✅ Check if OpenAI API key is set: This is the #1 cause of issues

  echo $OPENAI_API_KEY  # Should show your API key

• ✅ Verify API key is valid: Test with OpenAI's API directly
• ✅ Check API key has sufficient credits: Ensure your OpenAI account has available credits

"Authentication failed" errors:

• The OpenAI API key is missing or invalid
• Set the environment variable: export OPENAI_API_KEY="your-key"

Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some 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 ISC License. See the LICENSE file for details.

Support

For support, please open an issue in the GitHub repository or contact the maintainer.