OpenRouter Multimodal Server

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An MCP (Model Context Protocol) server that provides chat and image analysis capabilities through OpenRouter.ai's diverse model ecosystem. This server combines text chat functionality with powerful image analysis capabilities.

Features

• Text Chat:

  • Direct access to all OpenRouter.ai chat models
  • Support for simple text and multimodal conversations
  • Configurable temperature and other parameters

• Image Generation: ✨ NEW

  • Generate images using OpenRouter models (e.g., Google Gemini)
  • Support for custom aspect ratios (1:1, 16:9, 9:16, etc.)
  • Optional Cloudinary upload for permanent storage
  • Automatic retry logic with exponential backoff
  • Multiple image generation in single request

• Image Analysis:

  • Analyze single images with custom questions
  • Process multiple images simultaneously
  • Automatic image resizing and optimization
  • Support for various image sources (local files, URLs, data URLs)

• Model Selection:

  • Search and filter available models
  • Validate model IDs
  • Get detailed model information
  • Support for default model configuration

• Performance Optimization:

  • Smart model information caching
  • Exponential backoff for retries
  • Automatic rate limit handling

What's New in 1.5.0

• Improved OS Compatibility:

  • Enhanced path handling for Windows, macOS, and Linux
  • Better support for Windows-style paths with drive letters
  • Normalized path processing for consistent behavior across platforms

• MCP Configuration Support:

  • Cursor MCP integration without requiring environment variables
  • Direct configuration via MCP parameters
  • Flexible API key and model specification options

• Robust Error Handling:

  • Improved fallback mechanisms for image processing
  • Better error reporting with specific diagnostics
  • Multiple backup strategies for file reading

• Image Processing Enhancements:

  • More reliable base64 encoding for all image types
  • Fallback options when Sharp module is unavailable
  • Better handling of large images with automatic optimization

Installation

Option 1: Install via npm

npm install -g @stabgan/openrouter-mcp-multimodal

Option 2: Run via Docker

docker run -i -e OPENROUTER_API_KEY=your-api-key-here stabgandocker/openrouter-mcp-multimodal:latest

Quick Start Configuration

Prerequisites

1. Get your OpenRouter API key from OpenRouter Keys
2. Choose a default model (optional)

MCP Configuration Options

Add one of the following configurations to your MCP settings file (e.g., cline_mcp_settings.json or claude_desktop_config.json):

Option 1: Using npx (Node.js)

{
  "mcpServers": {
    "openrouter": {
      "command": "npx",
      "args": ["-y", "@stabgan/openrouter-mcp-multimodal"],
      "env": {
        "OPENROUTER_API_KEY": "your-api-key-here",
        "DEFAULT_MODEL": "qwen/qwen2.5-vl-32b-instruct:free"
      }
    }
  }
}

Option 2: Using uv (Python Package Manager)

{
  "mcpServers": {
    "openrouter": {
      "command": "uv",
      "args": ["run", "-m", "openrouter_mcp_multimodal"],
      "env": {
        "OPENROUTER_API_KEY": "your-api-key-here",
        "DEFAULT_MODEL": "qwen/qwen2.5-vl-32b-instruct:free"
      }
    }
  }
}

Option 3: Using Docker

{
  "mcpServers": {
    "openrouter": {
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "-i",
        "-e",
        "OPENROUTER_API_KEY=your-api-key-here",
        "-e",
        "DEFAULT_MODEL=qwen/qwen2.5-vl-32b-instruct:free",
        "stabgandocker/openrouter-mcp-multimodal:latest"
      ]
    }
  }
}

Option 4: Using Smithery (recommended)

{
  "mcpServers": {
    "openrouter": {
      "command": "smithery",
      "args": ["run", "stabgan/openrouter-mcp-multimodal"],
      "env": {
        "OPENROUTER_API_KEY": "your-api-key-here",
        "DEFAULT_MODEL": "qwen/qwen2.5-vl-32b-instruct:free"
      }
    }
  }
}

Examples

For comprehensive examples of how to use this MCP server, check out the examples directory. We provide:

• JavaScript examples for Node.js applications
• Python examples with interactive chat capabilities
• Code snippets for integrating with various applications

Each example comes with clear documentation and step-by-step instructions.

Dependencies

This project uses the following key dependencies:

• @modelcontextprotocol/sdk: ^1.8.0 - Latest MCP SDK for tool implementation
• openai: ^4.89.1 - OpenAI-compatible API client for OpenRouter
• sharp: ^0.33.5 - Fast image processing library
• axios: ^1.8.4 - HTTP client for API requests
• node-fetch: ^3.3.2 - Modern fetch implementation

Node.js 18 or later is required. All dependencies are regularly updated to ensure compatibility and security.

Available Tools

mcp_openrouter_chat_completion

Send text or multimodal messages to OpenRouter models:

use_mcp_tool({
  server_name: "openrouter",
  tool_name: "mcp_openrouter_chat_completion",
  arguments: {
    model: "google/gemini-2.5-pro-exp-03-25:free", // Optional if default is set
    messages: [
      {
        role: "system",
        content: "You are a helpful assistant.",
      },
      {
        role: "user",
        content: "What is the capital of France?",
      },
    ],
    temperature: 0.7, // Optional, defaults to 1.0
  },
});

For multimodal messages with images:

use_mcp_tool({
  server_name: "openrouter",
  tool_name: "mcp_openrouter_chat_completion",
  arguments: {
    model: "anthropic/claude-3.5-sonnet",
    messages: [
      {
        role: "user",
        content: [
          {
            type: "text",
            text: "What's in this image?",
          },
          {
            type: "image_url",
            image_url: {
              url: "https://example.com/image.jpg",
            },
          },
        ],
      },
    ],
  },
});