Openrouter Image MCP
The OpenRouter Image MCP Server provides powerful image analysis capabilities for AI agents, supports multiple visual models, and can analyze visual content such as photos, web page screenshots, and mobile application interfaces
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What is the OpenRouter Image MCP Server?
This is a server based on the Model Context Protocol (MCP), specifically designed to provide image analysis capabilities for AI assistants. By integrating multiple advanced visual models on the OpenRouter platform (such as Claude, Gemini, GPT - 4 Vision, etc.), it allows your AI assistant to 'see' and understand image content, including photos, screenshots, charts, and documents.How to use this service?
It's very simple to use: 1) Get an OpenRouter API key; 2) Add MCP server settings to your AI assistant configuration; 3) Restart your AI assistant to start using the image analysis function. The server will automatically start and connect to the OpenRouter API.Use cases
This service is particularly suitable for scenarios that require image understanding capabilities, such as analyzing web page screenshots, extracting text from documents, reviewing UI designs, understanding chart data, analyzing product photos, and interpreting technical charts.Main Features
Multi - model Support
Supports multiple visual models on the OpenRouter platform, including Claude, Gemini, GPT - 4 Vision, etc. You can choose the most suitable model according to your needs.
Flexible Input Methods
Supports three image input methods: file path, URL link, and Base64 - encoded data, meeting different usage scenarios.
Specialized Analysis Tools
Provides specialized analysis tools for web page screenshots and mobile application interfaces, capable of in - depth analysis such as layout analysis and user experience evaluation.
Cost Optimization
Supports free and paid models. Users can choose the most cost - effective solution according to their needs.
Easy Integration
Seamlessly integrates with mainstream AI assistants (Claude Desktop, Cursor, Cline, etc.), with simple and fast configuration.
Advantages
๐ Ready to use: No need to manually start the server after configuration
๐ฐ Flexible cost: Provides free model options, reducing the usage threshold
๐ฏ Professional analysis: Provides specialized analysis tools for different scenarios
๐ง Easy to integrate: Supports multiple mainstream AI assistant platforms
๐ฑ Cross - platform compatibility: Supports Windows, macOS, and Linux systems
Limitations
๐ Requires network connection: Depends on the OpenRouter API service
๐ Requires API key: Must register an OpenRouter account to obtain the key
๐ Image size limit: Maximum support for a single image is 10MB
โฑ๏ธ Response time: Depends on network conditions and model processing speed
How to Use
Get an API Key
Visit the OpenRouter official website to register an account and get an API key
Choose an Installation Method
It is recommended to use the npx method (no installation required) or the global installation method
Configure the AI Assistant
Add MCP server settings to your AI assistant configuration file
Set Environment Variables
Configure the OpenRouter API key and the selected model
Restart and Use
Restart your AI assistant. Now you can use the image analysis function
Usage Examples
Web Design Review
Analyze web page screenshots to evaluate user experience and design issues
Document Text Extraction
Extract text content from scanned documents or pictures
Product Image Analysis
Analyze product photos to describe product features and details
Technical Chart Interpretation
Understand technical charts and data visualization content
Mobile Application Interface Analysis
Review the user interface design of mobile applications
Frequently Asked Questions
Is this service free?
Which image formats are supported?
Do I need programming knowledge to use it?
Which AI assistant platforms are supported?
Will the image data be saved or shared?
How to handle large - size images?
Which model is recommended?
Related Resources
OpenRouter Official Website
Register an account and get an API key
GitHub Code Repository
View source code, submit issues, and participate in development
MCP Protocol Documentation
Understand the Model Context Protocol technical specifications
npm Package Page
View the latest version and installation instructions

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