Vision MCP

Vision MCP

Enables image analysis and understanding using Vision Language Models through OpenAI-compatible APIs. Supports analyzing images from URLs or local files with custom prompts.

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README

Vision MCP

MCP server for image analysis using Vision Language Models.

Quickstart

  1. Install uv (Python package manager):

    curl -LsSf https://astral.sh/uv/install.sh | sh
    
  2. Configure 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
OPENAI_API_KEY Yes API key for authentication
OPENAI_API_BASE Yes API base URL
OPENAI_MODEL Yes Model name for vision tasks

Available Tools

Tool Description
analyze_image 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 analyze
  • image_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.

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