Read Images

by catalystneuro

8 stars

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GitHub

About

Integrates with OpenRouter's vision models to enable image analysis and content extraction through natural language queries.

Details

Author: catalystneuro
Repository: catalystneuro/mcp_read_images
GitHub stars: 8
License: MIT License
Categories: Developer Tools, AI, API, Design, Media, Search, Infrastructure

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below
Plugin Name Read Images

Command (node, npx, python, etc.) read_images
Environment
- OPENROUTER_MODEL anthropic/claude-3.5-sonnet
- OPENROUTER_API_KEY your-api-key-here
Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "read images": {
            "env": {
                "OPENROUTER_MODEL": "anthropic/claude-3.5-sonnet",
                "OPENROUTER_API_KEY": "your-api-key-here"
            },
            "args": [],
            "command": "read_images"
        }
    }
}

JSON

{
    "mcpServers": {
        "read images": {
            "env": {
                "OPENROUTER_MODEL": "anthropic/claude-3.5-sonnet",
                "OPENROUTER_API_KEY": "your-api-key-here"
            },
            "args": [],
            "command": "read_images"
        }
    }
}

JSON

{
    "mcpServers": {
        "read images": {
            "env": {
                "OPENROUTER_MODEL": "anthropic/claude-3.5-sonnet",
                "OPENROUTER_API_KEY": "your-api-key-here"
            },
            "args": [],
            "command": "read_images"
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "read images": {
            "env": {
                "OPENROUTER_MODEL": "anthropic/claude-3.5-sonnet",
                "OPENROUTER_API_KEY": "your-api-key-here"
            },
            "args": [],
            "command": "read_images"
        }
    }
}

JSON

{
    "mcpServers": {
        "read images": {
            "env": {
                "OPENROUTER_MODEL": "anthropic/claude-3.5-sonnet",
                "OPENROUTER_API_KEY": "your-api-key-here"
            },
            "args": [],
            "command": "read_images"
        }
    }
}

JSON

{
    "mcpServers": {
        "read images": {
            "env": {
                "OPENROUTER_MODEL": "anthropic/claude-3.5-sonnet",
                "OPENROUTER_API_KEY": "your-api-key-here"
            },
            "args": [],
            "command": "read_images"
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "read images": {
            "env": {
                "OPENROUTER_MODEL": "anthropic/claude-3.5-sonnet",
                "OPENROUTER_API_KEY": "your-api-key-here"
            },
            "args": [],
            "command": "read_images"
        }
    }
}

JSON

{
    "mcpServers": {
        "read images": {
            "env": {
                "OPENROUTER_MODEL": "anthropic/claude-3.5-sonnet",
                "OPENROUTER_API_KEY": "your-api-key-here"
            },
            "args": [],
            "command": "read_images"
        }
    }
}

JSON

{
    "mcpServers": {
        "read images": {
            "env": {
                "OPENROUTER_MODEL": "anthropic/claude-3.5-sonnet",
                "OPENROUTER_API_KEY": "your-api-key-here"
            },
            "args": [],
            "command": "read_images"
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "read images": {
            "env": {
                "OPENROUTER_MODEL": "anthropic/claude-3.5-sonnet",
                "OPENROUTER_API_KEY": "your-api-key-here"
            },
            "args": [],
            "command": "read_images"
        }
    }
}

JSON

{
    "mcpServers": {
        "read images": {
            "env": {
                "OPENROUTER_MODEL": "anthropic/claude-3.5-sonnet",
                "OPENROUTER_API_KEY": "your-api-key-here"
            },
            "args": [],
            "command": "read_images"
        }
    }
}

JSON

{
    "mcpServers": {
        "read images": {
            "env": {
                "OPENROUTER_MODEL": "anthropic/claude-3.5-sonnet",
                "OPENROUTER_API_KEY": "your-api-key-here"
            },
            "args": [],
            "command": "read_images"
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "read images": {
            "env": {
                "OPENROUTER_MODEL": "anthropic/claude-3.5-sonnet",
                "OPENROUTER_API_KEY": "your-api-key-here"
            },
            "args": [],
            "command": "read_images"
        }
    }
}

JSON

{
    "mcpServers": {
        "read images": {
            "env": {
                "OPENROUTER_MODEL": "anthropic/claude-3.5-sonnet",
                "OPENROUTER_API_KEY": "your-api-key-here"
            },
            "args": [],
            "command": "read_images"
        }
    }
}

JSON

{
    "mcpServers": {
        "read images": {
            "env": {
                "OPENROUTER_MODEL": "anthropic/claude-3.5-sonnet",
                "OPENROUTER_API_KEY": "your-api-key-here"
            },
            "args": [],
            "command": "read_images"
        }
    }
}

From the repository

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

  }

});

`analyze_image`

Analyze an image using a selected vision model. Parameters: image_path (string, required), question (string, optional), model (string, optional, specifies the model to use for analysis)

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "read images": {
            "env": {
                "OPENROUTER_MODEL": "anthropic/claude-3.5-sonnet",
                "OPENROUTER_API_KEY": "your-api-key-here"
            },
            "args": [],
            "command": "read_images"
        }
    }
}

Linux

{
    "env": {
        "OPENROUTER_MODEL": "anthropic/claude-3.5-sonnet",
        "OPENROUTER_API_KEY": "your-api-key-here"
    },
    "args": [],
    "command": "read_images"
}

Macos

{
    "env": {
        "OPENROUTER_MODEL": "anthropic/claude-3.5-sonnet",
        "OPENROUTER_API_KEY": "your-api-key-here"
    },
    "args": [],
    "command": "read_images"
}

Windows

{
    "env": {
        "OPENROUTER_MODEL": "anthropic/claude-3.5-sonnet",
        "OPENROUTER_API_KEY": "your-api-key-here"
    },
    "args": [],
    "command": "read_images"
}

Analyze images using OpenRouter's vision models. Requires an OpenRouter API key.

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.

npm install @catalystneuro/mcp_read_images

The server requires an OpenRouter API key. You can get one fromOpenRouter.

Add the server to your MCP settings file (usually located at~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.jsonfor 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": [] } } }

The server provides a single toolanalyze_imagethat 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 } });

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)

The following OpenRouter models have been tested:

- anthropic/claude-3.5-sonnet
- anthropic/claude-3-opus-20240229

- Automatic image resizing and optimization
- Configurable model selection
- Support for custom questions about images
- Detailed error messages
- Automatic JPEG conversion and quality optimization

- 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.

git clone https://github.com/catalystneuro/mcp_read_images.git cd mcp_read_images npm install npm run build

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Read Images

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Setting up with Highlight

Setting up with Cursor

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Setting up with Claude Desktop

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Setting up with Windsurf

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Setting up with Cline

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Setting up with Goose

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From the repository

`analyze_image`

Claude Desktop / Cursor

Linux

Macos

Windows

Install

About

Details

Jump to

Setting up with Highlight

From the repository

analyze_image

Claude Desktop / Cursor

Linux

Macos

Windows

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