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MCP Read Images

by catalystneuro
OverviewInspectNewSchemaRelated ServersScore
JavaScript
Hybrid
MIT License
8

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.

This server cannot be installed

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

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