This n8n workflow automates the process of scraping LinkedIn profiles and company pages using Bright Data MCP tools, extracting meaningful insights, and leveraging AI models for content generation. It is designed for users who want to gather LinkedIn data efficiently and convert it into structured, usable formats.
The flow begins with manual trigger testing, where URLs for individual LinkedIn profiles and company pages are set. The workflow then uses Bright Data MCP Client nodes to scrape detailed profile and company data, including about sections and stories, via specified URLs. Extracted data is sent through webhook requests for real-time processing.
Further, the workflow employs AI models like Google Gemini and language models for analyzing and generating stories or summaries based on the scraped data. The information is processed, combined, and stored as JSON files locally, which allows for easy access and further analysis.
This workflow is highly practical for market researchers, sales teams, or content creators who need to automate data collection from LinkedIn, enabling quicker insights and enabling data-driven decisions or content generation with minimal manual effort.
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