Provides image analysis capabilities using OpenAI's Vision Language Models, enabling analysis and understanding of image content from files or URLs through the analyze_image tool.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Vision MCPdescribe this image: https://example.com/photo.jpg"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Vision MCP
MCP server for image analysis using Vision Language Models.
Quickstart
Install
uv(Python package manager):curl -LsSf https://astral.sh/uv/install.sh | shConfigure your MCP client (e.g., Claude Desktop):
Go to Claude > Settings > Developer > Edit Config > claude_desktop_config.json:
{
"mcpServers": {
"Vision": {
"command": "uvx",
"args": ["vision-mcp"],
"env": {
"OPENAI_API_KEY": "your-api-key",
"OPENAI_API_BASE": "https://api.openai.com",
"OPENAI_MODEL": "gpt-4o"
}
}
}
}Environment Variables
Variable | Required | Description |
| Yes | API key for authentication |
| Yes | API base URL |
| Yes | Model name for vision tasks |
Available Tools
Tool | Description |
| Analyze images using Vision Language Model |
analyze_image
Analyze and understand image content from files or URLs.
Parameters:
prompt(str): The text prompt describing what to analyzeimage_source(str): Image URL or local file path
Supported formats: JPEG, PNG, WebP
License
MIT
Acknowledgments
This project is inspired by MiniMax-Coding-Plan-MCP by MiniMax AI.
Resources
Looking for Admin?
Admins can modify the Dockerfile, update the server description, and track usage metrics. If you are the server author, to access the admin panel.