MCP_Multi_Agent_Stock_Recommendation

📈 AI-Powered Stock Analysis Dashboard An end-to-end multi-agent stock analysis system for the Indian Stock Market (NSE). It uses a FastAPI backend (AI agents via LangChain + LangGraph) and a Streamlit frontend (interactive dashboard) to generate trading insights. 🚀 Features FastAPI Backend 4 specialized agents: 🔍 Stock Finder, 📊 Market Data, 📰 News Analyst, 💰 Price Recommender Orchestrated by a LangGraph supervisor Powered by Azure OpenAI GPT‑4 + Bright Data MCP tools Streamlit Frontend Real-time agent status simulation Final Buy/Sell/Hold recommendations Filters for strategy, market cap, and sectors 🛠 Tech Stack FastAPI, LangChain, LangGraph Azure OpenAI, Bright Data MCP Streamlit, Plotly, Pandas ⚡ Quick Start Bash # Backend cd backend pip install -r requirements.txt uvicorn main:app --reload --port 8000 # Frontend cd frontend pip install -r requirements.txt streamlit run app.py API runs at: http://localhost:8000 Dashboard at: http://localhost:8501 🧠 How It Works User query → Supervisor agent Tasks delegated: Stock Finder → Market Data → News → Price Recommender Agents return insights → Final structured recommendation Streamlit displays real-time progress + results 🙏 Credits Inspired by this [YouTube video on](https://www.youtube.com/watch?v=NF2aRqIlYNE) MCP | Multi-Agent Stock Recommendation Project. 📜 License MIT License — free to use, fork, and modify.