MCP Read Images
An MCP server for analyzing images using OpenRouter vision models. This server provides a simple interface to analyze images using various vision models like Claude-3.5-sonnet and Claude-3-opus through the OpenRouter API.
Installation
npm install @catalystneuro/mcp_read_images
Configuration
The server requires an OpenRouter API key. You can get one from OpenRouter.
Add the server to your MCP settings file (usually located at ~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json for VSCode):
{
"mcpServers": {
"read_images": {
"command": "read_images",
"env": {
"OPENROUTER_API_KEY": "your-api-key-here",
"OPENROUTER_MODEL": "anthropic/claude-3.5-sonnet" // optional, defaults to claude-3.5-sonnet
},
"disabled": false,
"autoApprove": []
}
}
}
Usage
The server provides a single tool analyze_image that can be used to analyze images:
// Basic usage with default model
use_mcp_tool({
server_name: "read_images",
tool_name: "analyze_image",
arguments: {
image_path: "/path/to/image.jpg",
question: "What do you see in this image?" // optional
}
});
// Using a specific model for this call
use_mcp_tool({
server_name: "read_images",
tool_name: "analyze_image",
arguments: {
image_path: "/path/to/image.jpg",
question: "What do you see in this image?",
model: "anthropic/claude-3-opus-20240229" // overrides default and settings
}
});
Model Selection
The model is selected in the following order of precedence:
- Model specified in the tool call (
modelargument) - Model specified in MCP settings (
OPENROUTER_MODELenvironment variable) - Default model (anthropic/claude-3.5-sonnet)
Supported Models
The following OpenRouter models have been tested:
- anthropic/claude-3.5-sonnet
- anthropic/claude-3-opus-20240229
Features
- Automatic image resizing and optimization
- Configurable model selection
- Support for custom questions about images
- Detailed error messages
- Automatic JPEG conversion and quality optimization
Error Handling
The server handles various error cases:
- Invalid image paths
- Missing API keys
- Network errors
- Invalid model selections
- Image processing errors
Each error will return a descriptive message to help diagnose the issue.
Development
To build from source:
git clone https://github.com/catalystneuro/mcp_read_images.git
cd mcp_read_images
npm install
npm run build
License
MIT License. See LICENSE for details.