# 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. - **Type:** MCP server - **Install:** `agentstack add mcp-ratnesh-181998-build-agentic-ai-and-gen-ai-agents-with-mcp` - **Verified:** Yes β€” security-reviewed for prompt injection and unsafe behavior - **Seller:** [Ratnesh-181998](https://agentstack.voostack.com/s/ratnesh-181998) - **Installs:** 0 - **Category:** [Databases](https://agentstack.voostack.com/c/databases) - **Latest version:** 0.1.0 - **License:** MIT - **Upstream author:** [Ratnesh-181998](https://github.com/Ratnesh-181998) - **Source:** https://github.com/Ratnesh-181998/Build-Agentic-AI-and-Gen-AI-Agents-with-MCP - **Website:** https://www.youtube.com/watch?v=96G7FLab8xc | https://www.youtube.com/watch?v=Dqp_b8GHLXU ## Install ```sh agentstack add mcp-ratnesh-181998-build-agentic-ai-and-gen-ai-agents-with-mcp ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About --- --- # 10 Python AI/ML libraries - πŸ”’ **NumPy** πŸ‘‰ [🌐Official Website](https://numpy.org/) [πŸ“˜ Documentation](https://numpy.org/doc/) - 🐼 **Pandas** πŸ‘‰ [🌐Official Website](https://pandas.pydata.org/) [πŸ“˜ Documentation](https://pandas.pydata.org/docs/) - πŸ“Š **Scikit-Learn** πŸ‘‰ [🌐Official Website](https://scikit-learn.org/) [πŸ“˜ Documentation](https://scikit-learn.org/stable/) - πŸš€ **XGBoost** πŸ‘‰ [🌐Official Website](https://xgboost.readthedocs.io/en/latest/) [πŸ“˜ Documentation](https://xgboost.readthedocs.io/en/stable/) - ⚑ **LightGBM** πŸ‘‰ [🌐Official Website](https://lightgbm.readthedocs.io/en/stable/) [πŸ“˜ Documentation](https://lightgbm.readthedocs.io/en/stable/) - 🧠 **TensorFlow** πŸ‘‰ [🌐Official Website](https://www.tensorflow.org/) [πŸ“˜ Documentation](https://www.tensorflow.org/learn) - 🎯 **Keras** πŸ‘‰ [🌐Official Website](https://keras.io/) [πŸ“˜ Documentation](https://keras.io/guides/) - πŸ”₯ **PyTorch** πŸ‘‰ [🌐Official Website](https://pytorch.org/) [πŸ“˜ Documentation](https://docs.pytorch.org/) - πŸ€– **Transformers (Hugging Face)** πŸ‘‰ [🌐Official Website](https://huggingface.co/) [πŸ“˜ Documentation](https://huggingface.co/docs/transformers/en/index) - 🧩 **spaCy** πŸ‘‰ [🌐Official Website](https://spacy.io/) [πŸ“˜ Documentation](https://github.com/explosion/spacy-layout) - Complete Agentic AI Course In 10 Hours- Langchain, Langgraph, RAG,Vectorless RAG, Guardrails,Evals : https://www.youtube.com/watch?v=rV3HJ4LEZ7k --- # 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 - Live Demo & Topics in Details Coming Soon ### 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 --- # [Model Context Protocol (MCP) – The USB-C for AI Applications](https://github.com/Ratnesh-181998/Build-Agentic-AI-and-Gen-AI-Agents-with-MCP/blob/main/Model%20Context%20Protocol%20(MCP)%20%E2%80%93%20The%20USB-C%20for%20AI%20Applications.pdf) --- # [Just explored an incredible book on Model Context Protocol (MCP)](https://github.com/Ratnesh-181998/Build-Agentic-AI-and-Gen-AI-Agents-with-MCP/blob/main/Mastering%20Model%20Context%20Protocol%20.pdf) β€” and honestly, it completely reshaped how I think about the future of Agentic AI. - For years, AI systems have been powerful individually, but fragmented when it comes to collaboration, context-sharing, scalability, and orchestration. - MCP changes that. - This book explains how MCP is becoming the foundational communication layer for next-generation AI ecosystems β€” enabling AI agents, tools, servers, and workflows to operate with shared context, adaptive intelligence, modularity, and secure multi-agent coordination. ## Why MCP matters for the future of AI: --- ## πŸ“œ **License** **Licensed under the MIT License** - Feel free to fork and build upon this innovation! πŸš€ --- # πŸ“ž **CONTACT & NETWORKING** πŸ“ž ## πŸ’Ό Professional Networks [](https://www.linkedin.com/in/ratneshkumar1998/) [](https://github.com/Ratnesh-181998) [](https://x.com/RatneshS16497) [](https://share.streamlit.io/user/ratnesh-181998) [](mailto:rattudacsit2021gate@gmail.com) [](https://medium.com/@rattudacsit2021gate) [](https://stackoverflow.com/users/32068937/ratnesh-kumar) ## πŸš€ AI/ML & Data Science [AI/ML 1620+ Problem Solved](https://github.com/Ratnesh-181998/DSML) [](https://share.streamlit.io/user/ratnesh-181998) [](https://huggingface.co/RattuDa98) [](https://www.kaggle.com/rattuda) ## πŸ’» Competitive Programming [Including all coding plateform's 5000+ Problems/Questions solved](https://github.com/Ratnesh-181998/Algorithms-and-Data-Structures) [](https://leetcode.com/u/Ratnesh_1998/) [](https://www.hackerrank.com/profile/rattudacsit20211) [](https://www.codechef.com/users/ratnesh_181998) [](https://codeforces.com/profile/Ratnesh_181998) [](https://www.geeksforgeeks.org/profile/ratnesh1998) [](https://www.hackerearth.com/@ratnesh138/) [](https://www.interviewbit.com/profile/rattudacsit2021gate_d9a25bc44230/) --- ## πŸ“Š **GitHub Stats & Metrics** πŸ“Š --- ## Source & license This open-source MCP server is cataloged on AgentStack and links to its original source β€” we do not rehost the code. - **Author:** [Ratnesh-181998](https://github.com/Ratnesh-181998) - **Source:** [Ratnesh-181998/Build-Agentic-AI-and-Gen-AI-Agents-with-MCP](https://github.com/Ratnesh-181998/Build-Agentic-AI-and-Gen-AI-Agents-with-MCP) - **License:** MIT - **Homepage:** https://www.youtube.com/watch?v=96G7FLab8xc | https://www.youtube.com/watch?v=Dqp_b8GHLXU Install and usage instructions live in the source repository linked above. ## Pricing - **Free** β€” Free ## Security capabilities Automated source analysis of v0.1.0 β€” what this tool can access: - **Network access:** no - **Filesystem access:** no - **Shell / process execution:** no - **Environment & secrets:** no - **Dynamic code execution:** no *"Yes" means the capability is present in the source β€” more access means more to trust, not that it is unsafe.* ## Versions - **0.1.0** β€” security scan: passed β€” Imported from the upstream source. ## Links - Listing page: https://agentstack.voostack.com/l/mcp-ratnesh-181998-build-agentic-ai-and-gen-ai-agents-with-mcp - Seller: https://agentstack.voostack.com/s/ratnesh-181998 - Browse the marketplace: https://agentstack.voostack.com/browse --- Listed on AgentStack β€” the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.