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MCP server · RAG

Image Analysis Server

Analyze images and videos by providing URLs or local file paths. Gain insights and detailed descriptions of image content using advanced AI models. Enhance your applications with high-precision image recognition and video analysis capabilities.

Unclaimed last commit a year ago rag
34Low

Scored a month ago · breakdown

About Image Analysis Server

Image Analysis Server is an MCP server published by champierre in the RAG category: analyze images and videos by providing URLs or local file paths. Gain insights and detailed descriptions of image content using advanced AI models. Enhance your applications with high-precision image recognition and video analysis capabilities.

The repository has 8 stars and 8 forks, with the last commit a year ago. Six months or more without a commit doesn't mean the server is broken, but check the open issues before depending on it in production.

Install

From source
git clone https://github.com/champierre/image-mcp-server

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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README

image-mcp-server

日本語の README

smithery badge 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:
    • If the AI assistant has a Windows path (e.g., C:\...), it needs to convert it to a WSL path (e.g., /mnt/c/...) before passing it to the tool.
    • If the AI assistant has a WSL path, it can pass it as is.
  • If the server is running on Windows:
    • If the AI assistant has a WSL path (e.g., /home/user/...), it needs to convert it to a UNC path (e.g., \\wsl$\Distro\...) before passing it to the tool.
    • If the AI assistant has a Windows path, it can pass it as is.

Path conversion is the responsibility of the AI assistant (or its execution environment). The server will try to interpret the received path as is.

Note: Type Errors During Build

When running npm run build, you may see an error (TS7016) about missing TypeScript type definitions for the mime-types module.

src/index.ts:16:23 - error TS7016: Could not find a declaration file for module 'mime-types'. ...

This is a type checking error, and since the JavaScript compilation itself succeeds, it does not affect the server's execution. If you want to resolve this error, install the type definition file as a development dependency.

npm install --save-dev @types/mime-types
# or
yarn add --dev @types/mime-types

Development

# Run in development mode
npm run dev

License

MIT

README copy captured when this server was indexed; it may lag the repository. The original is authoritative.

Questions

About Image Analysis Server

How do I install Image Analysis Server?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is Image Analysis Server safe to use with an AI agent?

Its trust score is 34 out of 100 (low). It passes 1 of the 1 static security checks run so far. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Image Analysis Server still maintained?

The last commit was a year ago. That's long enough that you should check whether the maintainer is responding to issues before depending on it.