Huuthangntk Claude Vision Server
БесплатноНе проверенAnalyze images from multiple angles to extract detailed insights or quick summaries. Describe visu…
Описание
Analyze images from multiple angles to extract detailed insights or quick summaries. Describe visu…
README
A powerful Model Context Protocol (MCP) server that provides proactive deep analytical thinking using Anthropic's Claude Sonnet 4.5. This tool is designed to be called BEFORE writing code when new information arrives.
⚡ Core Concept: Think Before Code
Use this tool FIRST when new information arrives, BEFORE writing any code:
- 🐛 Error messages or stack traces
- 📝 User requirements or feature requests
- 💬 Code review feedback
- 🚀 Performance issues
- 🔒 Security alerts
- 📚 API documentation to integrate
- 🗄️ Database problems
- 💭 UX/UI feedback
- 🔄 Breaking changes in dependencies
- 🏗️ Architectural decisions
Workflow: New Info → Think Tool → Review Insights → Write Better Code
🌟 Features
Deep Think & Analysis (claude_think)
Provides intelligent insights, suggestions, and strategic guidance before code implementation. Perfect for:
- ✅ Understanding context deeply before acting
- ✅ Identifying potential pitfalls upfront
- ✅ Suggesting best practices from the start
- ✅ Offering alternative approaches
- ✅ Extracting key information for efficient implementation
- ✅ Strategic decision-making
- ✅ Problem-solving and architecture planning
Result: Fewer bugs, better code quality, faster development!
📋 Prerequisites
- Node.js 18+ or Bun
- Anthropic Claude API key (Get one here)
- MCP-compatible client (Cursor IDE, Claude Desktop, etc.)
🚀 Quick Start
1. Installation
cd claude-vision-mcp
bun install
# or
npm install
2. Configuration
The API key is configured when connecting to the MCP server (see Docker or Cursor setup below).
3. Build
bun run build
# or
npm run build
🐳 Docker Setup (Recommended)
Quick Start
cd claude-vision-mcp
# Create .env file with your API key
echo "ANTHROPIC_API_KEY=your-key-here" > .env
echo "CLAUDE_MODEL=claude-sonnet-4-20250514" >> .env
# Start container
docker-compose up -d
# Check status
docker ps | grep claude-vision
The container will auto-restart when Docker Desktop launches.
Docker Configuration
The server runs on http://localhost:8080/mcp with the following environment variables:
ANTHROPIC_API_KEY- Your Claude API key (required)CLAUDE_MODEL- Model to use (default: claude-sonnet-4-20250514)
🔧 Usage in Cursor IDE
Docker Connection (Recommended)
Add to your ~/.cursor/mcp.json or .cursor/mcp.json:
{
"mcpServers": {
"Claude Deep Think": {
"url": "http://localhost:8080/mcp?apiKey=YOUR_API_KEY&model=claude-sonnet-4-5-20250929"
}
}
}
Enable Proactive Thinking
Copy the .cursorrules file from this repo to your project root. This makes Cursor AI automatically use the think tool before writing code.
# From your project directory
cp claude-vision-mcp/.cursorrules .cursorrules
Tool Usage Pattern
Always use this pattern when new information arrives:
Use the claude_think tool to analyze: [NEW INFORMATION]
Context: [Current situation, tech stack, constraints]
Examples:
Error Message:
Use the claude_think tool to analyze:
Error: "TypeError: Cannot read property 'map' of undefined"
Context: React component rendering users from useState hook
New Feature:
Use the claude_think tool:
Requirement: Add dark mode toggle to header
Context: Next.js 14, need to check if ThemeContext exists
Performance Issue:
Use the claude_think tool:
Issue: Homepage renders 50+ times, parent causing all children to re-render
Context: useState for theme in Header, passed via props to 20+ children
📚 Examples
Example 1: Analyzing Technical Decisions
Use the claude_think tool to analyze:
"I'm building a real-time chat application. Should I use WebSockets, SSE, or HTTP polling?"
Context: Need to support 100K concurrent users, prioritize ease of implementation
Expected Output: Comprehensive comparison with pros, cons, and recommendations
Example 2: Architecture Planning
Use the claude_think tool to evaluate:
"What's the best way to structure a multi-tenant SaaS application?"
Context: PostgreSQL database, Node.js backend, 50-100 tenants expected
Example 3: Best Practices
Use the claude_think tool:
"Review this approach to handling user sessions in a Next.js app"
Context: Using JWT tokens, storing in localStorage, concerned about security
🛠️ Development
Project Structure
claude-vision-mcp/
├── src/
│ └── index.ts # Main MCP server implementation
├── .smithery/
│ └── index.cjs # Built server (generated)
├── package.json # Dependencies and scripts
├── tsconfig.json # TypeScript configuration
├── smithery.yaml # Smithery deployment config
├── Dockerfile # Docker container definition
├── docker-compose.yml # Docker Compose configuration
└── README.md # This file
Available Scripts
bun run build/npm run build- Compile TypeScriptbun run dev/npm run dev- Development server with hot reload
🔒 Security Best Practices
- Never commit API keys - Always use environment variables
- Use .gitignore - Ensure
.envfiles are ignored - Rotate keys regularly - Update API keys periodically
- Review tool calls - Keep manual approval enabled in Cursor
- Use development environments - Test with non-production data
📦 Docker Management
# Start container
docker-compose up -d
# View logs
docker logs claude-vision-mcp-server -f
# Restart container
docker-compose restart
# Stop container
docker-compose down
# Rebuild and restart
docker-compose up -d --build
🐛 Troubleshooting
Issue: Server not connecting in Cursor
Solutions:
- Verify Docker container is running:
docker ps | grep claude-vision - Check container logs:
docker logs claude-vision-mcp-server - Restart Cursor IDE completely
- Verify API key in URL is correct
Issue: API key errors
Solutions:
- Ensure key starts with
sk-ant- - Test key at: https://console.anthropic.com/
- Check environment variables in container
- Verify URL parameter format
Issue: Container won't start
Solutions:
# Check logs
docker logs claude-vision-mcp-server
# Verify .env file
cat .env
# Rebuild from scratch
docker-compose down -v
docker-compose up -d --build
💡 Performance
With Bun runtime:
- ⚡ 4x faster package installs
- ⚡ 3-4x faster script execution
- 📦 Smaller Docker images
- 🚀 Faster cold starts
📖 Comprehensive Guides
- PROACTIVE_THINKING_WORKFLOW.md - Complete workflow guide with before/after examples
- THINK_TOOL_EXAMPLES.md - 10 real-world usage examples
- .cursorrules - Cursor IDE rules for automatic think-before-code pattern
💡 Why This Workflow?
Without Think Tool:
1. User reports error
2. AI writes quick fix
3. Fix creates new bug
4. Multiple iterations needed
⏱️ Total: 30 minutes, 3 iterations
With Claude_Think Tool:
1. User reports error
2. AI analyzes with claude_think tool (20s)
3. AI writes comprehensive fix
4. Works correctly first time
⏱️ Total: 5 minutes, 1 iteration
Result: 6x faster, better quality, fewer bugs! 🎉
📄 License
MIT
🤝 Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
📞 Support
For issues or questions:
- Open an issue on GitHub
- Check the MCP Documentation
- Read the workflow guides in this repository
🙏 Acknowledgments
- Built with Anthropic Claude API
- Powered by Model Context Protocol
- Containerized with Bun
Установка Huuthangntk Claude Vision Server
У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.
▸ github.com/huuthangntk/claude-vision-mcp-serverFAQ
Huuthangntk Claude Vision Server MCP бесплатный?
Да, Huuthangntk Claude Vision Server MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для Huuthangntk Claude Vision Server?
Нет, Huuthangntk Claude Vision Server работает без API-ключей и переменных окружения.
Huuthangntk Claude Vision Server — hosted или self-hosted?
Доступен hosted-вариант: Unyly запускает сервер в облаке, локальная установка не обязательна.
Как установить Huuthangntk Claude Vision Server в Claude Desktop, Claude Code или Cursor?
Открой Huuthangntk Claude Vision Server на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
Похожие MCP
Fetch
Web content fetching and conversion for efficient LLM usage.
AWS KB Retrieval
Retrieval from AWS Knowledge Base using Bedrock Agent Runtime.
автор: modelcontextprotocolSpring AI MCP Server
Provides auto-configuration for setting up an MCP server in Spring Boot applications.
llm-analysis-assistant
A very streamlined mcp client that supports calling and monitoring stdio/sse/streamableHttp, and can also view request responses through the /logs page. It also
автор: xuzexin-hzCompare Huuthangntk Claude Vision Server with
Не уверен что выбрать?
Найди свой стек за 60 секунд
Автор?
Embed-бейдж для README
Похожее
Все в категории ai
