How I Built a Real-Time AI Stock Advisor Using Elasticsearch, MCP, and LLMs

This story was originally published on HackerNoon at: https://hackernoon.com/how-i-built-a-real-time-ai-stock-advisor-using-elasticsearch-mcp-and-llms. Build a pre-market stock analysis system using Elasticsearch, Airflow, and LLMs to surface momentum signals automatically. Check more stories related to tech-stories at: https://hackernoon.com/c/tech-stories. You can also check exclusive content about #ai-stock-analysis, #elasticsearch, #elasticsearch-stock-data, #mcp-trading-system, #llm-for-financial-analysis, #kibana-stock-dashboard, #airflow-trading-pipeline, #algorithmic-trading-system, and more. This story was written by: @gowtham448. Learn more about this writer by checking @gowtham448's about page, and for more stories, please visit hackernoon.com. This article walks through building an automated stock analysis pipeline that runs overnight and delivers pre-market insights. By combining data ingestion, sentiment analysis, technical indicators, and LLM-based synthesis through MCP tools, the system surfaces top momentum candidates before market open. The key takeaway is that structured pipelines can turn raw market data into actionable signals without relying on manual chart analysis.