n8n Market Data Feed


7 September 2026
Project codes are available at Github

This n8n worfklow sends a daily market brief to a Telegram group and Gmail recipients. It uses Yahoo Finance and CNBC as data sources, and the workflow is scheduled to run at 8:00 AM every weekday. The workflow fetches market data, formats it, and sends it to the specified channels.

Chatbot overview
The n8n workflow for the daily market brief

'Build Symbols List' node

The 'Build Symbols List' node constructs a list of stock symbols to fetch data for. The output is an array of symbols that will be processed in the subsequent nodes.

Chatbot overview
The 'Build Symbols List' node in the n8n workflow

Retrieving data from Yahoo Finance and CNBC RSS

Data is retrieved from Yahoo Finance using the HTTP Request node, which fetches indices data in JSON format. The CNBC RSS feed is accessed using the RSS Feed Read node, which retrieves the latest market news. The data from both sources is then processed and formatted for output.

Chatbot overview
The RSS node for news retrieval from CNBC
Sheets Get Row
Settings to configure the market indices
Class registry
Settings to configure the market headlines

Output

The processed data (after being processed by AI agent) is sent to both a Telegram group and Gmail recipients. The Telegram node uses the chat ID of the group to send the message, while the Gmail node sends an email with the market brief to specified recipients. The output includes formatted indices data and the latest market news headlines.

AI agent
Output sent to Telegram
AI agent
Output sent to Email

As seen, it first displays the market indices, followed by the latest market news headlines.


This was an interesting project to work on, as it involved integrating multiple data sources and automating the process of sending market updates to different platforms. The use of n8n made it easy to create a workflow that could handle the data retrieval, processing, and output in a seamless manner. It has also answered a question that I had many years back, which was how daily market news were sent by news agencies, stock brokers, etc at a specific time every day. This project has given me a better understanding of how to automate such processes and the potential of using n8n for various data integration tasks.