How to use n8n + OpenAI to build an automated content collection and publishing workflow: from zero to one in 30 minutes

Tutorial Objectives

In 30 minutes, use n8n to build a complete AI automated content collection and publishing workflow. From RSS scraping, AI excerpt rewriting to automatic publishing to blogs and social media, the entire process does not require writing a single line of back-end code.

What will you build?

• Automatic Content Collector: Regularly grab the latest content from RSS/API feeds
• AI summary rewriting module: Use OpenAI/DeepSeek to rewrite the original text into a structured summary
• Automatic publishing pipeline: automatically push processed content to blog draft box and social media
• Error Notification System: Automatically send Telegram notifications when workflow exceptions occur

Preparation list

• n8n account — self-host or use n8n.cloud (free version to complete this tutorial)
• OpenAI or DeepSeek API Key (choose one, GPT-4o-mini or DeepSeek-V3 is acceptable)
• Telegram Bot Token (for notifications, optional but recommended)
• API access to the target publishing platform (choose one from WordPress / Notion / Social Media)

Overall architecture

The entire workflow is disassembled into 4 modules, which can be connected in order. n8n’s visual node editor makes every step clearly visible.

Step 1: Build content collection trigger

Open the n8n editor and create a new workflow. Drag two nodes from the left node panel:

1. Schedule Trigger — Set to execute automatically at 08:00 and 20:00 every day
2. RSS Feed Read — Enter the RSS feed address you want to monitor

// Schedule Trigger
{
  "rule": {
    "interval": [{"field": "hour", "hoursInterval": 12}]
  }
}

// RSS Feed Read
{
  "url": "https://example.com/rss",
  "options": {
    "sendOnlyNew": true
  }
}

**** RSS， HTTP Request API， Hacker News API (https://hacker-news.firebaseio.com/v0/topstories.json).

Step 2: Configure AI content processing module

This is the "brain" of the entire workflow. Drag in an OpenAI or LangChain node and connect it to the output of the RSS reader.

Configure the system prompt words to let AI rewrite the original article into structured content:

{
  "model": "gpt-4o-mini",
  "messages": [
    {
      "role": "system",
 "content": "。，\n1. （150）\n2. 3-5 \n3. SEO （）\n\n JSON。"
    },
    {
      "role": "user",
      "content": "={{ $json["content"] }}"
    }
  ]
}

， model DeepSeek API 。DeepSeek-V3 ， GPT-4o-mini 。

， AI + + SEO 。

OpenAI API DeepSeek ，。

3

AI ，。 Code ， JavaScript Python

// n8n Code —
const item = $input.first().json;

//
if (item.summary && item.summary.length < 50) {
 throw new Error("，");
}

//
if (!item.tags || item.tags.length < 2) {
 item.tags = ["AI", ""];
}

//
return {
  title: item.seo_title || item.original_title,
  summary: item.summary,
  tags: item.tags.slice(0, 5),
  source_url: item.source_url,
  processed_at: new Date().toISOString()
};

4

，。 HTTP Request IF 。

Notion WordPress API

 A — Notion API → Notion （）
 B — WordPress API →
 C — Telegram Bot →

SEO+GEO Tip: Publishing through different channels can not only expand coverage, but also allow search engines to include your content faster.

If you need help, the n8n community already has many ready-made n8n for reference. If you haven't registered yet, you can register for a free account through n8n, which is also one of the most mature low-code automation tools currently.

Frequently Asked Questions (FAQ)

Q1: Is n8n free version enough?

Completely enough. The free version supports 2500 workflow executions/month, which is plenty for individual content creators. Upgrade to the paid version only if you require multi-user collaboration or higher execution quotas.

Q2: Will the content rewritten by AI be judged as spam by search engines?

The key is quality control. This tutorial has added checks such as summary length and originality to ensure that the output is not a simple translation of the original text. Paired with manual review, the effect is far better than pure AI batch generation.

Q3: Which one is more suitable for Chinese content production, DeepSeek or OpenAI?

DeepSeek is extremely cost-effective on Chinese tasks and is suitable for scenarios with limited budgets. OpenAI's GPT-4o-mini is more stable in instruction compliance and structured output. It is recommended to use OpenAI to build it in the early stage, and then switch some tasks to DeepSeek to reduce costs after stabilization.

SEO+GEO: FAQ structure meets GEO extraction preferences while covering long-tail search terms

Tool entry

For tool names that naturally appear in the text, the platform side will match the maintained tools library to generate a hover-card: n8n, OpenAI, ChatGPT, DeepSeek, LangGraph

Reference video/material

• n8n
• OpenAI API
• DeepSeek

Internal link guidance

• Someone has successfully practiced it: Indie Developer: n8n + OpenClaw Automation Workflow Earning $5,000/mo
• Newbies should read the tutorial first: Use OpenClaw to build an AI automatic collection system in 30 minutes: grab structured data from web pages