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Build Next Gen Ai Agents With MCP
Model Context Protocol (MCP) Bootcamp offers a deep dive into MCP architecture and its role in the Agentic AI ecosystem. Learn to build real-world, production-ready AI workflows using MCP with LangChain, LangGraph, and CrewAI through fully practical, project-based implementations.
创建于 1/12/2026
更新于 about 15 hours ago
README
Repository documentation and setup instructions
Build Agentic AI and Gen AI Agents with MCP
- Model Context Protocol (MCP) Bootcamp offers a deep dive into MCP architecture and its role in the Agentic AI ecosystem. Learn to build real-world, production-ready AI workflows using MCP with LangChain, LangGraph, and CrewAI through fully practical, project-based implementations.
- https://fastmcp.cloud/
Table of contents
Section 1 Model Context Protocol
Section 2 Getting Started With Claude Desktop And Cursor IDE
Section 3 Cursor IDE MCP Server Setup
Section 4 How to build Your Own MCP Client using Python and Google Gemini API
Section 5 How to build Docker MCP Server
Section 6 LangChain MCP Client using LangChain MCP Adapters
Section 7 MCP Client with Multiple Server Support
Section 8 MCP Server and Client using SSE
Section 9 Deploying MCP Server to AWS Cloud Platform
Section 10 Real Time Weather Agent using MCP and MCP Inspector
Section 11 Real Time Job Recommendation System
Section 12 StoryForge Agent
Section 13 Clinisight AI
Section 14 Build Agent with Google Development Kit ADK
📜 License
Licensed under the MIT License - Feel free to fork and build upon this innovation! 🚀
📞 CONTACT & NETWORKING 📞
💼 Professional Networks
🚀 AI/ML & Data Science
💻 Competitive Programming
📊 GitHub Stats & Metrics 📊
快速设置
此服务器的安装指南
安装包 （如果需要）
docker run -i Ratnesh-181998/Build-Next-Gen-AI-Agents-with-MCP
Cursor 配置 (mcp.json)
{
"mcpServers": {
"ratnesh-181998-build-next-gen-ai-agents-with-mcp": {
"command": "docker",
"args": [
"run",
"-i",
"Ratnesh-181998/Build-Next-Gen-AI-Agents-with-MCP"
]
}
}
}
作者服务器
其他服务器由 Ratnesh-181998