Automated Web Search, Extraction, and Summarization with Tavily and n8n

This workflow enables automated web searching, content extraction, and summarization leveraging the Tavily API integrated with n8n. It is designed to streamline data collection for research, content curation, or AI training by automating complex multi-step processes. The workflow begins with a trigger via a chat interface where a user provides a search query or topic. It then performs a web search using Tavily Search API with customizable parameters such as search depth, domain filters, and result limits. The top search result with the highest relevance score is selected, and detailed content extraction is executed via Tavily Extract API.

Furthermore, the workflow includes a step for filtering search results based on relevance scores, ensuring only highly relevant data proceeds. It also features an AI-powered content summarization node that condenses the extracted web content into an easy-to-read Markdown format using an OpenAI language model. The entire process can be adapted for various use cases, including research automation, competitor analysis, or content summarization for websites.

Practical scenarios include automating research workflows for journalists, marketing teams extracting competitor data, or AI models training with rich, relevant web content. The use of sticky notes throughout the workflow provides clear documentation and guidance for users unfamiliar with individual steps. Overall, this setup significantly reduces manual effort, ensures data quality, and accelerates decision-making processes.