
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.
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.
Installation
In SourceWeft
- Open Image Recongnition Mcp in the dashboard and add it to a workspace.
- 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:
⚠️ 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:
Response:
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
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
- ✅ 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
- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add some amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - 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
0Version history
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.