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

Get your OpenRouter API key from OpenRouter Keys
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"
            }
          }
        ]
      }
    ]
  }
});

This server cannot be installed

security - not tested

license - not found

quality - not tested

How are these scores calculated?

hybrid server

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

Provides chat and image analysis capabilities through OpenRouter.ai's diverse model ecosystem, enabling both text conversations and powerful multimodal image processing with various AI models.

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