
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
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image-mcp-server
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:
安装
npx -y @smithery/cli install @champierre/image-mcp-server --client claude配置
{
"mcpServers": {
"image-analysis": {
"command": "node",
"args": ["/path/to/image-mcp-server/dist/index.js"],
"env": {
"OPENAI_API_KEY": "your_openai_api_key"
}
}
}
}