MCP HydroCoder Vision
A local vision-language MCP server that enables Claude Code to perform image analysis, OCR, and UI-to-code generation using the Qwen3 VL 4B model via LM Studio. It provides privacy-focused visual processing by running entirely on the user's local hardware without external API dependencies.
README
MCP HydroCoder Vision
English Installation | 中文安装 | 中文 README
A vision-language MCP server that enables Claude Code to analyze images using Qwen3 VL 4B model running locally via LM Studio.
Features
- 🔍 Image Analysis - Describe images in detail
- 📝 Text Extraction (OCR) - Extract text from images in multiple languages
- 💻 UI to Code - Generate HTML/CSS/JS code from UI/design screenshots
- 🏠 100% Local - All processing happens on your machine, no cloud API needed
- ⚡ Fast - Qwen3 VL 4B runs efficiently on 8GB VRAM
Prerequisites
- LM Studio installed and running
- Qwen3 VL 4B model loaded in LM Studio
- Node.js 18+
Installation
1. Clone the repository
git clone https://github.com/hydroCoderClaud/mcp-hydrocoder-vision.git
cd mcp-hydrocoder-vision
2. Install dependencies
npm install
3. Build the project
npm run build
Configuration
1. Start LM Studio
- Open LM Studio
- Download and load
Qwen3-VL-4B-Instructmodel - Start the local server (default:
http://localhost:1234)
2. Configure Claude Code
Add to your ~/.claude/settings.json:
{
"mcpServers": {
"hydrocoder-vision": {
"command": "npx",
"args": ["-y", "mcp-hydrocoder-vision"],
"env": {
"LM_STUDIO_URL": "http://localhost:1234/v1/chat/completions",
"VISION_MODEL": "Qwen3-VL-4B-Instruct"
}
}
}
}
Usage
Available Tools
analyzeImage
Analyze an image and get a detailed description.
/analyzeImage imagePath: "C:/path/to/image.png" prompt: "What's in this image?"
extractText
Extract text from an image (OCR).
/extractText imagePath: "C:/path/to/document.png" language: "English"
describeForCode
Generate code from a UI/design screenshot.
/describeForCode imagePath: "C:/path/to/design.png" framework: "Vue"
Environment Variables
| Variable | Default | Description |
|---|---|---|
LM_STUDIO_URL |
http://localhost:1234/v1/chat/completions |
LM Studio API endpoint |
VISION_MODEL |
Qwen3-VL-4B-Instruct |
Model name to use |
Development
# Run in development mode (watch mode)
npm run dev
# Build for production
npm run build
# Start the built server
npm start
Troubleshooting
"Request failed: ECONNREFUSED"
- Make sure LM Studio is running
- Check that the local server is enabled
- Verify the
LM_STUDIO_URLis correct
"No response from model"
- Ensure Qwen3 VL 4B model is loaded in LM Studio
- Check LM Studio logs for errors
- Try a simpler prompt first
Image not found
- Use absolute paths
- Ensure the file exists and is accessible
- Check file permissions
License
MIT
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.