Automated Product Hunt Data Extraction with Bright Data MCP & Google Gemini AI

Overview

This workflow streamlines the extraction and structuring of Product Hunt search data by integrating Bright Data MCP and Google Gemini AI within n8n. It is triggered manually and orchestrates multiple advanced nodes for data retrieval, AI processing, and structured output.

Key Features

• Manual Trigger: Initiate the workflow on demand for flexible data extraction.
• Bright Data MCP Integration: Leverages MCP tools to perform Google searches and extract markdown data from Product Hunt.
• AI-Powered Processing: Utilizes Google Gemini AI via LangChain nodes to interpret and structure extracted content.
• Automated Data Structuring: Processes raw data into structured formats, ready for analysis or storage.
• File Output: Writes the final structured data to disk for easy access and further use.

Benefits

• Time Savings: Automates repetitive data extraction and structuring tasks, reducing manual effort.
• Enhanced Accuracy: AI-driven content parsing ensures high-quality, structured outputs.
• Seamless Integration: Combines multiple platforms and tools for a unified, efficient workflow.

Use Cases

• Market research and trend analysis on Product Hunt listings.
• Automated data collection for analytics or reporting.
• Enriching CRM or marketing databases with up-to-date product information.