Image Recongnition Mcp

io.github.shalevshalitPublished by GitHub account shalevshalitv1.0.0Updated Oct 24, 2026

MCP server for AI-powered image recognition and description using OpenAI vision models.

VerifiedSTDIODesktop onlyMedia & DesignAI & ML

Overview

AI-generated overview

A local MCP server that lets an assistant send an image URL to OpenAI vision models and get back a detailed written description.

What you can do
Analyze an image from a URL and return a detailed text description, using OpenAI vision models.
When to use it
Useful when you want an assistant to look at an image hosted at a public URL and describe its contents in words, without building your own vision integration.
Requirements
Runs locally via npx with Node.js 18+ and npm or yarn. Requires an OpenAI API key supplied in the OPENAI_API_KEY environment variable, and network access to fetch images and call the OpenAI API.
Before you install
The OPENAI_API_KEY secret is required and is the only way the server works; keep it out of shared configs. Image URLs are sent to OpenAI for analysis, and usage is billed to your OpenAI account, so sufficient credits are needed. The image URL is fetched by the server, so only point it at sources you trust.

Installation

In SourceWeft

  1. Open Image Recongnition Mcp in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

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:

json
{  "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:

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

Response:

json
{  "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
    bash
    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.

Source: README.md at commit 0f19b62

Tools

0
SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

1
  1. v1.0.0LatestSep 16, 2026

Score

40% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 days25 pts

    Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.

  • Auth declared10 pts

    Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.

  • Tools listed15 pts

    Answer tools/list without a credential, or ship a package that starts in a sandbox without one.

  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts

    Declare a license in the repository or the registry entry.