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Research-Based Article Generator with OpenAI and Web Search for High SEO Scores

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Last update 17 hours ago

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Generate research-backed article with n8n

Who’s it for

Content marketers, SEO teams, and founders who need fast, research-grounded blog posts or long-form articles—multi-language included. Works well for teams that want citations, outlines, and section-by-section drafting with minimal manual effort.

How it works / What it does

Use a Form to collects domain, keywords, and target language.

The workflow refines keywords, finds recent articles and authoritative citations, then synthesizes a master outline and loops through each section: generate search queries → fetch web results → summarize findings → write the section with the advanced model.

Finally, it aggregates all sections into a clean Markdown article. Optional delivery nodes (Email, Telegram) and an AI Agent are included but disabled by default.

How to set up

  1. Import the workflow JSON into n8n.
  2. Add your OpenAI credential
  3. Set simple_model / advanced_model in LLM Params

Requirements

  • n8n instance with outbound internet access.
  • OpenAI API access (Responses API + web_search_preview).
  • (Optional) Email/Telegram credentials if you want to deliver results async

How to customize the workflow

  • Edit prompts in LLM Params and Section Prompts to match tone, structure, and SEO style
  • Tweak recency and source rules in Search Articles / Search Citations.
  • Insert a human review step before “Write Section”, enable delivery nodes
  • Change working/output languages in the Language node