What is Openrouter Mcp Multimodal

openrouter-mcp-multimodal is an MCP server designed for OpenRouter, providing capabilities for text chat and image analysis through a diverse model ecosystem.

Use cases

Use cases include automated customer service chatbots, interactive educational tools, social media content analysis, and image-based question answering systems.

How to use

To use openrouter-mcp-multimodal, you can install it via npm or run it using Docker. Make sure to obtain your OpenRouter API key and configure the server as needed.

Key features

Key features include direct access to OpenRouter.ai chat models, support for multimodal conversations, image analysis with custom questions, model selection and validation, and performance optimizations such as caching and rate limit handling.

Where to use

openrouter-mcp-multimodal can be used in various fields such as customer support, content creation, image processing, and any application requiring interactive chat and image analysis capabilities.

OpenRouter MCP Multimodal Server

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 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"
            }
          }
        ]
      }
    ]
  }
});