servidor de imagen-mcp
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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:
- 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 AI assistant has a Windows path (e.g.,
-
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.
- If the AI assistant has a WSL path (e.g.,
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
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Reviews
user_i1w5EEvT
As a devoted user of image-mcp-server, I must say that champierre has created an exceptional tool for image processing. The server is incredibly efficient and easy to integrate into various projects. Its versatility with different programming languages and detailed documentation makes it a top choice for developers. Highly recommend checking out image-mcp-server!