Agentic AI With Langgraph And MCP Crash Course-Part 1

Code link: https://github.com/krishnaik06/Agentic-LanggraphCrash-course LangGraph is built for developers who want to build powerful, adaptable AI agents. Developers choose LangGraph for: Reliability and controllability. Steer agent actions with moderation checks and human-in-the-loop approvals. LangGraph persists context for long-running workflows, keeping your agents on course. Low-level and extensible. Build custom agents with fully descriptive, low-level primitives free from rigid abstractions that limit customization. Design scalable multi-agent systems, with each agent serving a specific role tailored to your use case. First-class streaming support. With token-by-token streaming and streaming of intermediate steps, LangGraph gives users clear visibility into agent reasoning and actions as they unfold in real time. Learn LangGraph basics¶ To get acquainted with LangGraph's key concepts and features, complete the following LangGraph basics tutorials series: Build a basic chatbot Add tools Add memory Add human-in-the-loop controls Customize state Time travel Timestamp: 00:00:00 Introduction And Agenda 00:03:37 Langgraph Projects Structure 00:11:15 Building Blocks Of LAnggraph 00:23:47 Building a Basic Chatbot 00:49:05 Building Chatbot With Tools 01:18:37 ReACT Agent Architecture 01:26:22 Adding Memory In Langgraph 01:35:00 Streaming In Langgraph 01:44:58 Human Feedback In the loop 01:52:42 MCP Server Scratch Implementation