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champierre/image-mcp-server

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本页由 AI 翻译,技术细节请以原文为准。 查看原文

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An MCP server that receives image URLs or local file paths and analyzes image content using the GPT-4o-mini model.

概览

An MCP server that receives image URLs or local file paths and analyzes image content using the GPT-4o-mini model. - Receives image URLs or local file paths as input and provides detailed analysis of the image content - High-precision image recognition and description using the GPT-4o-mini model - Image URL validity checking - Image loading from local files and Base64 encoding To install Image Analysis Server for Claude Desktop automatically via Smithery: To use this server, you need an OpenAI API key. Set the following environment variable: To use with tools like Cline, add the following settings to your MCP server configuration file: Add the following to cline_mcp_settings.json: Add the following to claude_desktop_config.json: Once the MCP server is configured, the following tools become available:

README

以下为原文 README 节选,完整内容请查看原文。

image-mcp-server

日本語の README

An MCP server that receives image URLs or local file paths and analyzes image content using the GPT-4o-mini model.

Features

  • Receives image URLs or local file paths as input and provides detailed analysis of the image content
  • High-precision image recognition and description using the GPT-4o-mini model
  • Image URL validity checking
  • Image loading from local files and Base64 encoding

Installation

Installing via Smithery

To install Image Analysis Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @champierre/image-mcp-server --client claude

Manual Installation

# Clone the repository
git clone https://github.com/champierre/image-mcp-server.git # or your forked repository
cd image-mcp-server

# Install dependencies
npm install

# Compile TypeScript
npm run build

Configuration

To use this server, you need an OpenAI API key. Set the following environment variable:

OPENAI_API_KEY=your_openai_api_key

MCP Server Configuration

To use with tools like Cline, add the following settings to your MCP server configuration file:

For Cline

Add the following to cline_mcp_settings.json:

{
  "mcpServers": {
    "image-analysis": {
      "command": "node",
      "args": ["/path/to/image-mcp-server/dist/index.js"],
      "env": {
        "OPENAI_API_KEY": "your_openai_api_key"
      }
    }
  }
}

For Claude Desktop App

Add the following to claude_desktop_config.json:

{
  "mcpServers": {
    "image-analysis": {
      "command": "node",
      "args": ["/path/to/image-mcp-server/dist/index.js"],
      "env": {
        "OPENAI_API_KEY": "your_openai_api_key"
      }
    }
  }
}

Usage

Once the MCP server is configured, the following tools become available:

  • analyze_image: Receives an image URL and analyzes its content.
  • analyze_image_from_path: Receives a local file path and analyzes its content.

Usage Examples

Analyzing from URL:

Please analyze this image URL: https://example.com/image.jpg

Analyzing from local file path:

Please analyze this image: /path/to/your/image.jpg

Note: Specifying Local File Paths

When using the analyze_image_from_path tool, the AI assistant (client) must specify a valid file path in the environment where this server is running.

  • If the server is running on WSL:
在 GitHub 查看完整 README

安装

npx -y @smithery/cli install @champierre/image-mcp-server --client claude
新手?先看 mcpskill.org 教程 →

配置

{ "mcpServers": { "image-analysis": { "command": "node", "args": ["/path/to/image-mcp-server/dist/index.js"], "env": { "OPENAI_API_KEY": "your_openai_api_key" } } } }