Vision Mcp Server | 图片分析 Mcp

by Markusbetter

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GitHub Website

Media

About

This MCP addresses the visual recognition limitations of text-based models by enabling accurate image description and identification, making it excellent for AI-assisted reference design interface analysis.

Explore

- Support for local image files and online image URLs
- Intelligent image analysis based on ModelScope AI models
- Full compatibility with MCP protocol
- TypeScript support with complete type definitions

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below

Plugin Name Vision Mcp Server | 图片分析 Mcp

Command (node, npx, python, etc.)

Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "vision mcp server | \u56fe\u7247\u5206\u6790 mcp": {
            "vision-mcp-server": {
                "command": "npx",
                "args": [
                    "-y",
                    "vision-mcp-server"
                ],
                "env": {
                    "MODELSCOPE_TOKEN": "your_modelscope_token_here",
                    "MODELSCOPE_MODEL": "Qwen/Qwen3-VL-30B-A3B-Instruct"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "vision mcp server | \u56fe\u7247\u5206\u6790 mcp": {
            "vision-mcp-server": {
                "command": "npx",
                "args": [
                    "-y",
                    "vision-mcp-server"
                ],
                "env": {
                    "MODELSCOPE_TOKEN": "your_modelscope_token_here",
                    "MODELSCOPE_MODEL": "Qwen/Qwen3-VL-30B-A3B-Instruct"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "vision mcp server | \u56fe\u7247\u5206\u6790 mcp": {
            "vision-mcp-server": {
                "command": "npx",
                "args": [
                    "-y",
                    "vision-mcp-server"
                ],
                "env": {
                    "MODELSCOPE_TOKEN": "your_modelscope_token_here",
                    "MODELSCOPE_MODEL": "Qwen/Qwen3-VL-30B-A3B-Instruct"
                }
            }
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "vision mcp server | \u56fe\u7247\u5206\u6790 mcp": {
            "vision-mcp-server": {
                "command": "npx",
                "args": [
                    "-y",
                    "vision-mcp-server"
                ],
                "env": {
                    "MODELSCOPE_TOKEN": "your_modelscope_token_here",
                    "MODELSCOPE_MODEL": "Qwen/Qwen3-VL-30B-A3B-Instruct"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "vision mcp server | \u56fe\u7247\u5206\u6790 mcp": {
            "vision-mcp-server": {
                "command": "npx",
                "args": [
                    "-y",
                    "vision-mcp-server"
                ],
                "env": {
                    "MODELSCOPE_TOKEN": "your_modelscope_token_here",
                    "MODELSCOPE_MODEL": "Qwen/Qwen3-VL-30B-A3B-Instruct"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "vision mcp server | \u56fe\u7247\u5206\u6790 mcp": {
            "vision-mcp-server": {
                "command": "npx",
                "args": [
                    "-y",
                    "vision-mcp-server"
                ],
                "env": {
                    "MODELSCOPE_TOKEN": "your_modelscope_token_here",
                    "MODELSCOPE_MODEL": "Qwen/Qwen3-VL-30B-A3B-Instruct"
                }
            }
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "vision mcp server | \u56fe\u7247\u5206\u6790 mcp": {
            "vision-mcp-server": {
                "command": "npx",
                "args": [
                    "-y",
                    "vision-mcp-server"
                ],
                "env": {
                    "MODELSCOPE_TOKEN": "your_modelscope_token_here",
                    "MODELSCOPE_MODEL": "Qwen/Qwen3-VL-30B-A3B-Instruct"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "vision mcp server | \u56fe\u7247\u5206\u6790 mcp": {
            "vision-mcp-server": {
                "command": "npx",
                "args": [
                    "-y",
                    "vision-mcp-server"
                ],
                "env": {
                    "MODELSCOPE_TOKEN": "your_modelscope_token_here",
                    "MODELSCOPE_MODEL": "Qwen/Qwen3-VL-30B-A3B-Instruct"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "vision mcp server | \u56fe\u7247\u5206\u6790 mcp": {
            "vision-mcp-server": {
                "command": "npx",
                "args": [
                    "-y",
                    "vision-mcp-server"
                ],
                "env": {
                    "MODELSCOPE_TOKEN": "your_modelscope_token_here",
                    "MODELSCOPE_MODEL": "Qwen/Qwen3-VL-30B-A3B-Instruct"
                }
            }
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "vision mcp server | \u56fe\u7247\u5206\u6790 mcp": {
            "vision-mcp-server": {
                "command": "npx",
                "args": [
                    "-y",
                    "vision-mcp-server"
                ],
                "env": {
                    "MODELSCOPE_TOKEN": "your_modelscope_token_here",
                    "MODELSCOPE_MODEL": "Qwen/Qwen3-VL-30B-A3B-Instruct"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "vision mcp server | \u56fe\u7247\u5206\u6790 mcp": {
            "vision-mcp-server": {
                "command": "npx",
                "args": [
                    "-y",
                    "vision-mcp-server"
                ],
                "env": {
                    "MODELSCOPE_TOKEN": "your_modelscope_token_here",
                    "MODELSCOPE_MODEL": "Qwen/Qwen3-VL-30B-A3B-Instruct"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "vision mcp server | \u56fe\u7247\u5206\u6790 mcp": {
            "vision-mcp-server": {
                "command": "npx",
                "args": [
                    "-y",
                    "vision-mcp-server"
                ],
                "env": {
                    "MODELSCOPE_TOKEN": "your_modelscope_token_here",
                    "MODELSCOPE_MODEL": "Qwen/Qwen3-VL-30B-A3B-Instruct"
                }
            }
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "vision mcp server | \u56fe\u7247\u5206\u6790 mcp": {
            "vision-mcp-server": {
                "command": "npx",
                "args": [
                    "-y",
                    "vision-mcp-server"
                ],
                "env": {
                    "MODELSCOPE_TOKEN": "your_modelscope_token_here",
                    "MODELSCOPE_MODEL": "Qwen/Qwen3-VL-30B-A3B-Instruct"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "vision mcp server | \u56fe\u7247\u5206\u6790 mcp": {
            "vision-mcp-server": {
                "command": "npx",
                "args": [
                    "-y",
                    "vision-mcp-server"
                ],
                "env": {
                    "MODELSCOPE_TOKEN": "your_modelscope_token_here",
                    "MODELSCOPE_MODEL": "Qwen/Qwen3-VL-30B-A3B-Instruct"
                }
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "vision mcp server | \u56fe\u7247\u5206\u6790 mcp": {
            "vision-mcp-server": {
                "command": "npx",
                "args": [
                    "-y",
                    "vision-mcp-server"
                ],
                "env": {
                    "MODELSCOPE_TOKEN": "your_modelscope_token_here",
                    "MODELSCOPE_MODEL": "Qwen/Qwen3-VL-30B-A3B-Instruct"
                }
            }
        }
    }
}

From the repository

``bash npm install -g vision-mcp-server`Then in your client configuration:`json { "mcpServers": { "vision-mcp-server": { "command": "vision-mcp-server", "env": { "MODELSCOPE_TOKEN": "your_modelscope_token_here", "MODELSCOPE_MODEL": "Qwen/Qwen3-VL-30B-A3B-Instruct" } } } }

bash

npm install vision-mcp-server





Then in your client configuration:

json

{

  "mcpServers": {

    "vision-mcp-server": {

      "command": "node",

      "args": ["node_modules/vision-mcp-server/dist/index.js"],

      "env": {

        "MODELSCOPE_TOKEN": "your_modelscope_token_here",

        "MODELSCOPE_MODEL": "Qwen/Qwen3-VL-30B-A3B-Instruct"

      }

    }

  }

}



Before using, you need to set the following environment variables:



- MODELSCOPE_TOKEN: ModelScope API key (required)

  - Get it from: ModelScope → Profile → API Token

- MODELSCOPE_MODEL: Model name to use (optional, default is "Qwen/Qwen3-VL-30B-A3B-Instruct")

  - Supports other vision models, such as: Qwen/Qwen2-VL-7B-Instruct
javascript

// Analyze local image

{

  "name": "analyze_image",

  "arguments": {

    "image": "/path/to/your/image.jpg",

    "prompt": "Please describe the content of this image"

  }

}



// Analyze online image

{

  "name": "analyze_image",

  "arguments": {

    "image": "https://example.com/image.jpg",

    "prompt": "What objects are in this image?"

  }

}

`analyze_image`

分析图片内容并提供详细描述

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "vision mcp server | \u56fe\u7247\u5206\u6790 mcp": {
            "vision-mcp-server": {
                "command": "npx",
                "args": [
                    "-y",
                    "vision-mcp-server"
                ],
                "env": {
                    "MODELSCOPE_TOKEN": "your_modelscope_token_here",
                    "MODELSCOPE_MODEL": "Qwen/Qwen3-VL-30B-A3B-Instruct"
                }
            }
        }
    }
}

McpServers

{
    "vision-mcp-server": {
        "command": "npx",
        "args": [
            "-y",
            "vision-mcp-server"
        ],
        "env": {
            "MODELSCOPE_TOKEN": "your_modelscope_token_here",
            "MODELSCOPE_MODEL": "Qwen/Qwen3-VL-30B-A3B-Instruct"
        }
    }
}

English | 中文 ---

中文

一个用于图片分析的 MCP (Model Context Protocol) 服务器，支持图片内容分析和描述。例如当你在客户端的模型只支持文字输入，这时你可以使用视觉模型mcp来弥补。这个项目采用了魔搭社区免费的视觉模型Qwen3-VL-30B-A3B-Instruct（你也可以在配置中，使用魔搭社区自行更换为自己想要的视觉模型）。

功能特点

- 支持本地图片文件和在线图片 URL - 基于魔搭社区 AI 模型的智能图像分析 - 完全兼容 MCP 协议 - TypeScript 支持，提供完整的类型定义

安装

方式一：使用 npx（推荐）

无需预先安装，在客户端填写以下内容npx 会自动下载并运行最新版本： ``

json
{
  "mcpServers": {
    "vision-mcp-server": {
      "command": "npx",
      "args": [
        "-y",
        "vision-mcp-server"
      ],
      "env": {
        "MODELSCOPE_TOKEN": "your_modelscope_token_here",
        "MODELSCOPE_MODEL": "Qwen/Qwen3-VL-30B-A3B-Instruct"
      }
    }
  }
}



方式二：全局安装

bash
npm install -g vision-mcp-server



然后在客户端配置中：

json
{
  "mcpServers": {
    "vision-mcp-server": {
      "command": "vision-mcp-server",
      "env": {
        "MODELSCOPE_TOKEN": "your_modelscope_token_here",
        "MODELSCOPE_MODEL": "Qwen/Qwen3-VL-30B-A3B-Instruct"
      }
    }
  }
}



方式三：本地安装

bash
npm install vision-mcp-server



然后在客户端配置中：

json
{
  "mcpServers": {
    "vision-mcp-server": {
      "command": "node",
      "args": ["node_modules/vision-mcp-server/dist/index.js"],
      "env": {
        "MODELSCOPE_TOKEN": "your_modelscope_token_here",
        "MODELSCOPE_MODEL": "Qwen/Qwen3-VL-30B-A3B-Instruct"
      }
    }
  }
}



环境变量配置


在使用前，需要设置以下环境变量：

-

MODELSCOPE_TOKEN

: 魔搭社区的 API 密钥（必需）
  - 获取方式：访问 魔搭社区 → 个人中心 → API令牌
-

MODELSCOPE_MODEL

: 使用的模型名称（可选，默认为 "Qwen/Qwen3-VL-30B-A3B-Instruct"）
  - 支持其他视觉模型，如：

Qwen/Qwen2-VL-7B-Instruct



使用示例

javascript
// 分析本地图片
{
  "name": "analyze_image",
  "arguments": {
    "image": "/path/to/your/image.jpg",
    "prompt": "请描述这张图片的内容"
  }
}

// 分析在线图片
{
  "name": "analyze_image",
  "arguments": {
    "image": "https://example.com/image.jpg",
    "prompt": "这张图片中有哪些物体？"
  }
}



API 参考


analyze_image


分析图片内容并提供详细描述。

参数:
-

image

 (string): 图片 URL 或本地文件路径
-

prompt

 (string, 可选): 对图片的问题或分析要求，默认为 "请描述这张图片的内容"

返回:
图片内容的详细文本描述。

开发


构建

bash
npm run build



测试

bash
npm test



贡献


欢迎提交 Issue 和 Pull Request！

许可证


MIT

更新日志


1.0.0

- 初始版本发布
- 支持图片分析功能
- 兼容 MCP 协议

---

English


A Vision Analysis MCP (Model Context Protocol) Server that supports image content analysis and description.

Features


- Support for local image files and online image URLs
- Intelligent image analysis based on ModelScope AI models
- Full compatibility with MCP protocol
- TypeScript support with complete type definitions

Installation


Option 1: Using npx (Recommended)


No need to pre-install, npx will automatically download and run the latest version:

json
{
  "mcpServers": {
    "vision-mcp-server": {
      "command": "npx",
      "args": [
        "-y",
        "vision-mcp-server"
      ],
      "env": {
        "MODELSCOPE_TOKEN": "your_modelscope_token_here",
        "MODELSCOPE_MODEL": "Qwen/Qwen3-VL-30B-A3B-Instruct"
      }
    }
  }
}



Option 2: Global Installation

bash
npm install -g vision-mcp-server



Then in your client configuration:

json
{
  "mcpServers": {
    "vision-mcp-server": {
      "command": "vision-mcp-server",
      "env": {
        "MODELSCOPE_TOKEN": "your_modelscope_token_here",
        "MODELSCOPE_MODEL": "Qwen/Qwen3-VL-30B-A3B-Instruct"
      }
    }
  }
}



Option 3: Local Installation

bash
npm install vision-mcp-server



Then in your client configuration:

json
{
  "mcpServers": {
    "vision-mcp-server": {
      "command": "node",
      "args": ["node_modules/vision-mcp-server/dist/index.js"],
      "env": {
        "MODELSCOPE_TOKEN": "your_modelscope_token_here",
        "MODELSCOPE_MODEL": "Qwen/Qwen3-VL-30B-A3B-Instruct"
      }
    }
  }
}



Environment Variables Configuration


Before using, you need to set the following environment variables:

-

MODELSCOPE_TOKEN

: ModelScope API key (required)
  - Get it from: ModelScope → Profile → API Token
-

MODELSCOPE_MODEL

: Model name to use (optional, default is "Qwen/Qwen3-VL-30B-A3B-Instruct")
  - Supports other vision models, such as:

Qwen/Qwen2-VL-7B-Instruct



Usage Examples

javascript
// Analyze local image
{
  "name": "analyze_image",
  "arguments": {
    "image": "/path/to/your/image.jpg",
    "prompt": "Please describe the content of this image"
  }
}

// Analyze online image
{
  "name": "analyze_image",
  "arguments": {
    "image": "https://example.com/image.jpg",
    "prompt": "What objects are in this image?"
  }
}



API Reference


analyze_image


Analyze image content and provide detailed description.

Parameters:
-

image

 (string): Image URL or local file path
-

prompt

 (string, optional): Question or analysis requirement for the image, default is "Please describe the content of this image"

Returns:
Detailed text description of the image content.

Development


Build

bash
npm run build



Test

bash
npm test

Contributing

Issues and Pull Requests are welcome!

License

MIT

Changelog

1.0.0

- Initial release - Image analysis support - MCP protocol compatibility

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About

Explore

Setting up with Highlight

From the repository

analyze_image

Claude Desktop / Cursor

McpServers

中文

功能特点

安装

方式一：使用 npx（推荐）

方式二：全局安装

方式三：本地安装

环境变量配置

使用示例

API 参考

analyze_image

开发

构建

测试

贡献

许可证

更新日志

1.0.0

English

Features

Installation

Option 1: Using npx (Recommended)

Option 2: Global Installation

Option 3: Local Installation

Environment Variables Configuration

Usage Examples

API Reference

analyze_image

Development

Build

Test

Contributing

License

Changelog

1.0.0

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