LangGraph Multi-Agent AI System
As AI assistants evolve from simple chat interfaces to autonomous workers, developers need robust frameworks to handle complex, multi-domain workflows (such as querying academic knowledge bases, managing GitHub repos, and handling calendar/email productivity). Traditional monolithic prompts fail when scaling across diverse toolsets.
We set out to build a clean, production-ready architecture that bridges autonomous multi-agent orchestration with a responsive, full-stack dashboard—giving users a unified command center powered by specialized AI agents.
Orchestration & Logic: LangGraph, LangChain Core, Claude 3.5 Sonnet (ChatAnthropic)
Vector Database & RAG: Qdrant Vector Cloud, FastEmbed
Tool Protocols: Custom MCP (Model Context Protocol) servers using FastMCP
Backend: FastAPI, Uvicorn, Python
Frontend: React, Vite, modern CSS dark-theme dashboard with real-time state route indicators and animated agent badges
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