ai.smithery/huuthangntk-claude-vision-mcp-server
AI 与智能体by huuthangntk
可从多个角度分析图像,提取详细洞察或快速摘要,并生成清晰的视觉内容描述。
什么是 ai.smithery/huuthangntk-claude-vision-mcp-server?
可从多个角度分析图像,提取详细洞察或快速摘要,并生成清晰的视觉内容描述。
README
Claude Deep Think MCP Server
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
常见问题
ai.smithery/huuthangntk-claude-vision-mcp-server 是什么?
可从多个角度分析图像,提取详细洞察或快速摘要,并生成清晰的视觉内容描述。
相关 Skills
Claude接口
by anthropics
面向接入 Claude API、Anthropic SDK 或 Agent SDK 的开发场景,自动识别项目语言并给出对应示例与默认配置,快速搭建 LLM 应用。
✎ 想把Claude能力接进应用或智能体,用claude-api上手快、兼容Anthropic与Agent SDK,集成路径清晰又省心
RAG架构师
by alirezarezvani
聚焦生产级RAG系统设计与优化,覆盖文档切块、检索链路、索引构建、召回评估等关键环节,适合搭建可扩展、高准确率的知识库问答与检索增强应用。
✎ 面向RAG落地,把知识库、向量检索和生成链路系统串联起来,做架构设计时更清晰,也更少踩坑。
多智能体架构
by alirezarezvani
聚焦多智能体系统架构设计,梳理 Supervisor、Swarm、分层和 Pipeline 等模式,覆盖角色定义、通信协作与性能评估,适合规划稳健可扩展的 AI agent 编排方案。
✎ 帮你系统解决多智能体应用的架构设计与协同编排难题,适合构建复杂 AI 工作流,成熟度高、社区认可也很亮眼。
相关 MCP Server
顺序思维
编辑精选by Anthropic
Sequential Thinking 是让 AI 通过动态思维链解决复杂问题的参考服务器。
✎ 这个服务器展示了如何让 Claude 像人类一样逐步推理,适合开发者学习 MCP 的思维链实现。但注意它只是个参考示例,别指望直接用在生产环境里。
知识图谱记忆
编辑精选by Anthropic
Memory 是一个基于本地知识图谱的持久化记忆系统,让 AI 记住长期上下文。
✎ 帮 AI 和智能体补上“记不住”的短板,用本地知识图谱沉淀长期上下文,连续对话更聪明,数据也更可控。
by deusdata
持久化的代码库知识图谱,可跨会话保留上下文,在 session 重启或上下文压缩后仍能继续使用。
✎ 专治 AI 编程助手“会话失忆”,把代码库沉淀为持久知识图谱,重启或压缩上下文后也能无缝续上开发状态。