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Vision MCP Server | 图片分析 MCP

@Markusbetter

代码仓库

基本信息

分类

媒体与设计

传输方式

stdio

作者

Markusbetter

提交者

Markus Lee

关于 Vision MCP Server | 图片分析 MCP

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.

#vision#image-analysis#mcp

Vision MCP Server | 图片分析 MCP 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "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"
      }
    }
  }
}

Vision MCP Server | 图片分析 MCP 工具

1

分析图片内容并提供详细描述

概览

What is Vision Mcp Server | 图片分析 Mcp?

A Vision Analysis MCP server that provides image content analysis and description. It bridges text-only AI models with vision capabilities by using the free ModelScope vision model Qwen3-VL-30B-A3B-Instruct (configurable to other ModelScope vision models).

How to use Vision Mcp Server | 图片分析 Mcp?

Install via npx, global npm, or local npm. Configure in your MCP client with the environment variable MODELSCOPE_TOKEN (required) and optional MODELSCOPE_MODEL. Invoke the analyze_image tool with an image parameter (URL or local path) and an optional prompt.

Key features of Vision Mcp Server | 图片分析 Mcp

  • Supports local image files and online image URLs
  • Uses ModelScope’s free AI vision models
  • Fully compatible with the MCP protocol
  • TypeScript support with complete type definitions

Use cases of Vision Mcp Server | 图片分析 Mcp

  • Add vision analysis to a text‑only AI client
  • Describe the content of any image (local or URL)
  • Identify objects or answer questions about an image

常见问题

1

What model does it use by default?

It uses the free ModelScope model Qwen3‑VL‑30B‑A3B‑Instruct. You can change it via `MODELSCOPE_MODEL`.

2

What are the requirements?

A ModelScope API token (`MODELSCOPE_TOKEN`) is required. Node.js and npm are needed for installation.

3

Does it support local images?

Yes, both local file paths and online URLs are supported as input.

4

How is data handled?

Images are sent to the ModelScope API for analysis (based on the configured model).

5

What transport does it use?

It follows the MCP protocol; the README shows stdio configuration in client settings.

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