LangGraph AI

About

This repository serves as an implementation guide for building sophisticated AI applications using LangGraph. It contains practical examples, tutorials, and production-ready implementations across multiple domains, including advanced retrieval-augmented generation (RAG) systems with adaptive routing and self-correction, Model Context Protocol (MCP) server and client development, complex AI workflow orchestration patterns, and interactive human-in-the-loop AI systems.

Key Features

• Orchestration patterns for complex AI workflows
• 21 GitHub stars
• Advanced Retrieval and Generation (RAG) agents
• Interactive Human-in-the-Loop AI systems
• Agentic RAG Systems with adaptive routing and self-correction
• Model Context Protocol (MCP) server and client implementations

Use Cases

• Implementing Model Context Protocol (MCP) for AI model interaction
• Developing Agentic RAG systems for intelligent information retrieval
• Building sophisticated AI applications with LangGraph