Intelligent Online Web Searcher

Researchers, analysts, business professionals, or anyone needing quick, in-depth web-based insights on complex topics. Automates AI-driven web research: takes a query, generates optimized searches via Brave API, ranks results, extracts article content, and compiles a detailed APA7-formatted report with analysis using Google Gemini. 1. Get free API keys: Google Gemini (AI Studio), Brave Search (api.search.brave.com free tier), RapidAPI Article Extractor (300 free/month). 2. In n8n, paste keys into HTTP nodes (X-Subscription-Token for Brave, X-RapidAPI-Key for extractor). 3. Switch Webhook to Production URL. 4. Test via Webhook Call node with 'Research Question' parameter. n8n account; API keys for Gemini, Brave Search, RapidAPI; internet access. Free tiers suffice for light use (e.g., Brave: unlimited free; Gemini: 15 RPM limit). Tweak AI prompts in LLM chains for domain-specific focus; swap Gemini for other models; adjust ranking criteria or add more search iterations; modify report structure in Research Reporter prompt; integrate with tools like email/Slack for notifications. Key Technologies: n8n Workflow Automation,Google Gemini AI (1.5 Flash model),Brave Web Search API,RapidAPI Article Extractor,HTTP Requests,JavaScript Code Nodes,Structured Output Parsers Automation Value: Saves hours of manual searching and reading by AI-optimizing queries and extracting key insights. Delivers expert-level, cited reports (APA7) with independent analysis, reducing bias and errors. Scales research for teams; handles complex queries with multi-step reasoning (e.g., chain-of-thought). Cost-effective: Uses free APIs; automates 80% of research workflow, boosting productivity by 5-10x. Enables real-time, time-aware analysis with current date integration for fresh insights. Best Practices: Use structured JSON outputs with auto-fixing parsers for reliable AI responses. Implement delays and loops for API rate limit compliance. Incorporate chain-of-thought prompting for better AI reasoning and query quality. Aggregate data via Code nodes before AI to handle variable inputs efficiently. Add error handling (e.g., retryOnFail on AI chains) for robustness.