Vision Mcp Server | 图片分析 Mcp

Name: Vision Mcp Server | 图片分析 Mcp
Author: Markusbetter

@Markusbetter

About 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

Basic information

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "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"
      }
    }
  }
}

Tools

分析图片内容并提供详细描述

Overview

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

FAQ from Vision Mcp Server | 图片分析 Mcp

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.

What are the requirements?

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

Does it support local images?

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

How is data handled?

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

What transport does it use?

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

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