ai-ml

OpenRouter Image Analysis

by jonathanjude

OpenRouter Image Analysis offers color analyze and image j compatibilities for advanced image analysis using vision mode

Provides image analysis capabilities through OpenRouter's vision models, supporting base64, file paths, and URLs with specialized tools for general analysis, webpage screenshot evaluation, and mobile app design assessment against platform guidelines.

github stars

4

Multiple vision model optionsSpecialized mobile design assessment toolsSupport for various image input formats

best for

  • / AI agents needing vision capabilities
  • / Developers building image analysis workflows
  • / UX designers evaluating interface designs
  • / Content creators analyzing visual assets

capabilities

  • / Analyze images from files, URLs, or base64 data
  • / Evaluate webpage screenshots for design and UX
  • / Assess mobile app designs against platform guidelines
  • / Choose from multiple vision models (Claude, Gemini, GPT-4 Vision)
  • / Process photos, diagrams, and visual content
  • / Generate detailed image descriptions and insights

what it does

Analyzes images using OpenRouter's vision models, supporting various input formats including file paths, URLs, and base64 data. Includes specialized tools for webpage screenshots and mobile app design evaluation.

about

OpenRouter Image Analysis is a community-built MCP server published by jonathanjude that provides AI assistants with tools and capabilities via the Model Context Protocol. OpenRouter Image Analysis offers color analyze and image j compatibilities for advanced image analysis using vision mode It is categorized under ai ml.

how to install

You can install OpenRouter Image Analysis in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

OpenRouter Image Analysis is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

# 🖼️🤖 OpenRouter Image MCP Server [![npm version](https://badge.fury.io/js/openrouter-image-mcp.svg)](https://badge.fury.io/js/openrouter-image-mcp) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) [![TypeScript](https://img.shields.io/badge/TypeScript-007ACC?logo=typescript&logoColor=white)](https://www.typescriptlang.org/) [![Node.js](https://img.shields.io/badge/Node.js-43853D?logo=node.js&logoColor=white)](https://nodejs.org/) **🔥 Supercharge your AI agents with powerful image analysis capabilities!** 🔥 A blazing-fast ⚡ MCP (Model Context Protocol) server that enables AI agents to **see and understand images** using OpenRouter's cutting-edge vision models. Perfect for screenshots, photos, diagrams, and any visual content! 📸✨
--- ## 🌟 What Makes This Special? - **🎯 Multi-Model Support**: Choose from Claude, Gemini, GPT-4 Vision, and more! - **🚀 Lightning Fast**: Built with TypeScript and optimized for performance - **🔧 Flexible Input**: Support for file paths, URLs, and base64 data - **💰 Cost-Effective**: Smart model selection for the best price-to-quality ratio - **🛡️ Production Ready**: Robust error handling, retries, and comprehensive logging - **🎨 Easy Integration**: Works seamlessly with Claude Code, Cline, Cursor, and more! --- ## 🚀 Quick Start ### Prerequisites 📋 - **Node.js** 18+ ⚡ - **OpenRouter API Key** 🔑 (Get one at [openrouter.ai](https://openrouter.ai)) - **Your favorite MCP client** 🤖 (Claude Code, Cline, etc.) ### Installation 📦 ```bash # 🌟 Option 1: Use immediately with npx (recommended) npx openrouter-image-mcp # 🚀 Option 2: Install globally for frequent use npm install -g openrouter-image-mcp # 🛠️ Option 3: Clone and build locally git clone https://github.com/JonathanJude/openrouter-image-mcp.git cd openrouter-image-mcp npm install npm run build npm install -g . ``` > **💡 Why npx is recommended**: No installation required, always gets the latest version, and works perfectly for MCP server usage! ### Configuration ⚙️ The MCP server requires an OpenRouter API key. You can configure it in several ways: #### **Method 1: Environment Variables (Recommended)** ```bash # 🔑 Set your API key export OPENROUTER_API_KEY=sk-or-v1-your-api-key-here # 🎯 Set model (uses free model by default) export OPENROUTER_MODEL=google/gemini-2.0-flash-exp:free ``` #### **Method 2: .env File** ```bash # 📋 Copy the environment template cp .env.example .env # ✏️ Edit with your credentials nano .env ``` Add your OpenRouter credentials to `.env`: ```bash # 🔑 Required OPENROUTER_API_KEY=sk-or-v1-your-api-key-here # 🆓 Model (FREE by default - great for getting started!) OPENROUTER_MODEL=google/gemini-2.0-flash-exp:free # 🎛️ Optional settings LOG_LEVEL=info MAX_IMAGE_SIZE=10485760 RETRY_ATTEMPTS=3 ``` #### **Method 3: Direct Configuration in MCP Client** Add the API key directly in your MCP client configuration (see examples below). --- ## 🏠 **Works Locally - No Restarts Needed!** 🎯 **🚀 HUGE ADVANTAGE**: This MCP server works perfectly locally with **zero manual intervention** once configured! No restarts, no manual server starts, no fiddling with settings. It just **works**! ✨ ### 🔄 **How It Works Automatically** 1. **🎯 Configure once** → Set up your MCP client one time 2. **🚀 Auto-launches** → Client starts the server automatically 3. **🔧 Connects** → Validates API and loads models instantly 4. **🛠️ Ready to use** → All 3 tools available immediately ### ⚡ **Local Setup Benefits** - **🔥 Fire-and-forget**: Set up once, forget forever - **⚡ Lightning startup**: ~5 seconds total ready time - **🔄 Persistent across restarts**: Survives laptop shutdowns - **📱 Cross-platform**: Works on any OS with Node.js - **🎯 Zero maintenance**: No babysitting required --- ## 🔧 MCP Configuration ### **Option 1: Using npx (Recommended - No Installation Required)** The easiest way to use this MCP server is with npx, which automatically downloads and runs the package without any installation: #### **For Claude Code** Add to `~/.claude.json`: ```json { "mcp": { "servers": { "openrouter-image": { "command": "npx", "args": ["openrouter-image-mcp"], "env": { "OPENROUTER_API_KEY": "sk-or-v1-your-api-key-here", "OPENROUTER_MODEL": "google/gemini-2.0-flash-exp:free" } } } } } ``` #### **For Claude Desktop** Add to `~/Library/Application Support/Claude/claude_desktop_config.json`: ```json { "mcpServers": { "openrouter-image": { "command": "npx", "args": ["openrouter-image-mcp"], "env": { "OPENROUTER_API_KEY": "sk-or-v1-your-api-key-here", "OPENROUTER_MODEL": "google/gemini-2.0-flash-exp:free" } } } } ``` #### **For Other MCP Clients** - **Cursor**: `~/.cursor/mcp.json` - **Cline**: `~/.cline/mcp.json` - **Windsurf**: MCP settings file - **Other agents**: Check your agent's MCP documentation **✨ Benefits of npx:** - 🚀 **No installation needed** - works immediately - 🔄 **Always latest version** - automatically updates - 📱 **Cross-platform** - works everywhere Node.js is installed - 🧹 **Clean system** - no global packages required ### **Option 2: Global Installation (For Frequent Users)** If you plan to use this MCP server frequently, install it globally: ```bash npm install -g openrouter-image-mcp ``` Then use this configuration: ```json { "mcp": { "servers": { "openrouter-image": { "command": "openrouter-image-mcp", "env": { "OPENROUTER_API_KEY": "sk-or-v1-your-api-key-here", "OPENROUTER_MODEL": "google/gemini-2.0-flash-exp:free" } } } } } ``` **Benefits of global installation:** - ⚡ **Faster startup** - no download time - 🌐 **Works offline** - once installed - 🔧 **Simpler command** - shorter configuration ### **Option 3: Local Development** If you cloned the repo locally for development: ```json { "mcpServers": { "openrouter-image": { "command": "node", "args": ["/path/to/openrouter-image-mcp/dist/index.js"], "env": { "OPENROUTER_API_KEY": "sk-or-v1-your-api-key-here", "OPENROUTER_MODEL": "google/gemini-2.0-flash-exp:free" } } } } ``` > **🎯 Pro Tip**: Replace the API key with your actual OpenRouter key. The free model works great for most use cases! > **💡 Recommendation**: Start with **npx** (Option 1) - it's the easiest and most reliable way to get started! ### 💡 **Pro Tips for Local Setup** #### **🎯 Path Management** - **Absolute paths work best**: `/path/to/openrouter-image-mcp/dist/index.js` - **Avoid relative paths**: May break when switching directories - **Use your actual path**: Update the examples with your real project location #### **🔧 Environment Variables** - **Set in `.env` file**: Keep your API key secure - **OR set in system**: `export OPENROUTER_API_KEY=sk-or-v1-...` - **Test quickly**: Run `OPENROUTER_API_KEY=... node dist/index.js` #### **🚀 Quick Verification** ```bash # 🔍 Test if server works export OPENROUTER_API_KEY=sk-or-v1-your-key export OPENROUTER_MODEL=google/gemini-2.5-flash-lite-preview-09-2025 node dist/index.js # ✅ Should see logs: "Starting OpenRouter Image MCP Server" ``` #### **🐛 Troubleshooting Local Issues** **❌ "Command not found"** ```bash # ✅ Use absolute path to node "$(which node)" "/path/to/openrouter-image-mcp/dist/index.js" ``` **❌ "File not found"** ```bash # ✅ Verify the built file exists ls -la /path/to/openrouter-image-mcp/dist/index.js # 📝 Rebuild if missing npm run build ``` **❌ "API key required"** ```bash # ✅ Check your environment variables echo $OPENROUTER_API_KEY # 🔧 Or create .env file echo "OPENROUTER_API_KEY=sk-or-v1-your-key" > .env ``` ### 🌟 **Local Development Workflow** 1. **🛠️ Build once**: `npm run build` 2. **⚙️ Configure once**: Add MCP config to your AI agent 3. **🔄 Restart agent**: Pick up the new configuration 4. **🎯 Use immediately**: No manual server management needed! --- ## 🔥 Usage Examples ### With Claude Code 🤖 Add this to your `~/.claude.json`: ```json { "mcp": { "servers": { "openrouter-image": { "command": "npx", "args": ["openrouter-image-mcp"], "env": { "OPENROUTER_API_KEY": "sk-or-v1-your-api-key-here", "OPENROUTER_MODEL": "google/gemini-2.0-flash-exp:free" } } } } } ``` ### With Claude Desktop 🖥️ Add this to your `claude_desktop_config.json`: ```json { "mcpServers": { "openrouter-image": { "command": "npx", "args": ["openrouter-image-mcp"], "env": { "OPENROUTER_API_KEY": "sk-or-v1-your-api-key-here", "OPENROUTER_MODEL": "google/gemini-2.0-flash-exp:free" } } } } ``` ### 🎯 Amazing Things You Can Do! ```bash # 📸 Analyze any screenshot "Analyze this screenshot: /path/to/screenshot.png" # 🔍 Extract text from images "What text do you see in this document: /path/to/scan.jpg" # 🎨 Review UI designs "Review this UI mockup for accessibility issues: /path/to/design.png" # 📱 Debug mobile apps "Analyze this mobile app screenshot for UX problems: /path/to/app.png" # 🌐 Analyze webpages "What can you tell me about this webpage: https://example.com/screenshot.png" ``` --- ## 🛠️ Available Tools ### 🖼️ `analyze_image` - General Image Analysis Perfect for photos, diagrams, charts, and general visual content! **Parameters:** - `type` 📁 Input type: `file`, `url`, or `base64` - `data` 📸 Image data (path, URL, or base64 string) - `prompt` 💭 Custom analysis prompt - `format` 📊 Output: `text` or `json` - `maxTokens` 🔢 Maximum response tokens (default: 4000) - `temperature` 🌡️ Creativity 0-2 (default: 0.1) ### 🌐 `analyze_webpage_screenshot` - Webpage Specialist Designed specifically for web page analysis and debugging! **Features:** - 🎯 Layout analysis - 📱 Content extraction - 🔗 Navi ---

FAQ

What is the OpenRouter Image Analysis MCP server?
OpenRouter Image Analysis is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for OpenRouter Image Analysis?
This profile displays 10 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.
MCP server reviews

Ratings

4.510 reviews
  • Shikha Mishra· Oct 10, 2024

    OpenRouter Image Analysis is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Piyush G· Sep 9, 2024

    We evaluated OpenRouter Image Analysis against two servers with overlapping tools; this profile had the clearer scope statement.

  • Chaitanya Patil· Aug 8, 2024

    Useful MCP listing: OpenRouter Image Analysis is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Sakshi Patil· Jul 7, 2024

    OpenRouter Image Analysis reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Ganesh Mohane· Jun 6, 2024

    I recommend OpenRouter Image Analysis for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Oshnikdeep· May 5, 2024

    Strong directory entry: OpenRouter Image Analysis surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Dhruvi Jain· Apr 4, 2024

    OpenRouter Image Analysis has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Rahul Santra· Mar 3, 2024

    According to our notes, OpenRouter Image Analysis benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Pratham Ware· Feb 2, 2024

    We wired OpenRouter Image Analysis into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Yash Thakker· Jan 1, 2024

    OpenRouter Image Analysis is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.