MCP Read Images

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:

  1. Model specified in the tool call (model argument)
  2. Model specified in MCP settings (OPENROUTER_MODEL environment variable)
  3. 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.

-
security - not tested
A
license - permissive license
-
quality - not tested

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

An MCP server for analyzing images using OpenRouter vision models, offering capabilities like automatic image resizing, model configuration, and handling custom queries about images.

  1. Installation
    1. Configuration
      1. Usage
        1. Model Selection
        2. Supported Models
      2. Features
        1. Error Handling
          1. Development
            1. License

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