Generate SEO-optimized blog content with Gemini, Scrapeless and Pinecone RAG

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. How it works This advanced automation builds a fully autonomous SEO blog writer using n8n, Scrapeless, LLMs, and Pinecone vector database. It’s powered by a Retrieval-Augmented Generation (RAG) system that collects high-performing blog content, stores it in a vector store, and then generates new blog posts based on that knowledge—endlessly. Part 1: Build a Knowledge Base from Popular Blogs - Scrape existing articles from a well-established writer (in this case, Mark Manson) using the Scrapeless node. - Extract content from blog pages and store it in Pinecone, a powerful vector database that supports similarity search. - Use Gemini Embedding 001 or any other supported embedding model to encode blog content into vectors. - Result: You’ll have a searchable vector store of expert-level content, ready to be used for content generation and intelligent search. Part 2: SERP Analysis & AI Blog Generation - Use Scrapeless' SERP node to fetch search results based on your keyword and search intent. - Send the results to an LLM (like Gemini, OpenRouter, or OpenAI) to generate a keyword analysis report in Markdown → then converted to HTML. - Extract long-tail keywords, search intent insights, and content angles from this report. - Feed everything into another LLM with access to your Pinecone-stored knowledge base, and generate a fully SEO-optimized blog post. Set up steps Prerequisites - Scrapeless API key !image.png(fileId:1757) - Pinecone account and index setup - An embedding model (Gemini, OpenAI, etc.) - n8n instance with Community Node: n8n-nodes-scrapeless installed Credential Configuration - Add your Scrapeless and Pinecone credentials in n8n under the "Credentials" tab - Choose embedding dimensions according to the model you use (e.g., 768 for Gemini Embedding 001) Key Highlights - Clones a real content creator: Replicates knowledge and writing style from top-performing blog authors. - Auto-scrapes hundreds of blog posts without being blocked. - Stores expert content in a vector DB to build a reusable knowledge base. - Performs real-time SERP analysis using Scrapeless to fetch and analyze search data. - Generates SEO blog drafts using RAG with detailed keyword intelligence. - Output includes: blog title, HTML summary report, long-tail keywords, and AI-written article body. RAG + SEO: The Future of Content Creation This template combines: - AI reasoning from large language models - Reliable data scraping from Scrapeless - Scalable storage via Pinecone vector DB - Flexible orchestration using n8n nodes This is not just an automation—it’s a full-stack SEO content machine that enables you to: - Build a domain-specific knowledge base - Run intelligent keyword research - Generate traffic-ready content on autopilot 💡 Use Cases - SaaS content teams cloning competitor success - Affiliate marketers scaling high-traffic blog production - Agencies offering automated SEO content services - AI researchers building personal knowledge bots - Writers automating first-draft generation with real-world tone