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
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Scrape existing articles from a well-established writer (in this case, Mark Manson) using the Scrapeless node.
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Extract content from blog pages and store it in Pinecone , a powerful vector database that supports similarity search.
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Use Gemini Embedding 001 or any other supported embedding model to encode blog content into vectors.
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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 .
Setup steps
Prerequisites
Credential Configuration
- Add your Scrapeless and Pinecone credentials in n8n under the "Credentials" tab
- Choose embedding dimensions according to the model you use (eg, 768 for Gemini Embedding 001)
Key Highlights
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Clones a real content creator : Replicates knowledge and writing style from top-performing blog authors.
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Auto-scrapes hundreds of blog posts without being blocked.
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Stores expert content in a vector DB to build a reusable knowledge base.
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Performs real-time SERP analysis using Scrapeless to fetch and analyze search data.
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Generates SEO blog drafts using RAG with detailed keyword intelligence.
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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:
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AI reasoning from large language models
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Reliable data scraping from Scrapeless
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Scalable storage via Pinecone vector DB
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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
