Offers deployment through Docker containers, with support for environment variables and seamless integration with MCP configurations.
Enables use of Google's Gemini models through OpenRouter for text chat and multimodal conversations, with support for vision capabilities and model customization.
Provides Node.js-based installation and execution options with NPX support for easy integration into MCP environments.
Supports Python-based installation and execution using UV package manager for those preferring Python environments.
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
Option 2: Run via Docker
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)
Option 2: Using uv (Python Package Manager)
Option 3: Using Docker
Option 4: Using Smithery (recommended)
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 implementationopenai
: ^4.89.1 - OpenAI-compatible API client for OpenRoutersharp
: ^0.33.5 - Fast image processing libraryaxios
: ^1.8.4 - HTTP client for API requestsnode-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:
For multimodal messages with images:
This server cannot be installed
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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