MCP (Model Context Protocol) is the unsung hero behind modern tool-using AI agents. In this video, we demystify how AI assistants like ChatGPT and Claude can securely and seamlessly interact with external tools, APIs, databases, calendars, file systems, and more using MCP. From internal MCP clients to external MCP servers, we explore how this open protocol turns static LLMs into dynamic, action-taking agents. You’ll also get a solid technical overview of JSON-RPC, transport layers, SDKs, and how to build your own tools using Python. Whether you're an AI engineer, system architect, or just AI-curious, this deep dive will transform your understanding of real-world AI integrations.
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📌 Timestamps
00:00 – Intro: Why MCP is a Game-Changer for AI
01:12 – What is MCP? (The AI Toolbelt Analogy)
02:45 – Real-World Benefits of MCP
03:52 – How MCP Works: Agents, Clients & Servers
07:11 – Understanding MCP Tools, Prompts, and Resources
07:30 – The Transport Layer & JSON-RPC 2.0 Overview
09:47 – Local vs. Remote MCP Servers Explained
10:29 – Implementing an MCP Server (Engineer’s POV)
12:08 – LLM Loop & Tool Invocation in Practice
12:40 – Final Thoughts & What’s Next for MCP
• System Design Interview Basics
• System Design Questions
• LLM
• Machine Learning Basics
• Microservices
• Emerging Tech
AWS Certification:
AWS Certified Cloud Practioner: • How to Pass AWS Certified Cloud Practition...
AWS Certified Solution Architect Associate: • How to Pass AWS Certified Solution Archite...
AWS Certified Solution Architect Professional: • How to Pass AWS Certified Solution Archite...
🔗 References:
Anthropic's MCP Protocol Introduction
https://www.anthropic.com/news/model-...
Official Python SDK (Anthropic)
https://github.com/anthropics/anthrop...
JSON-RPC 2.0 Spec
https://www.jsonrpc.org/specification
#mcp #ai #distributedsystems
