Content farming - : AI-powered blog automation for WordPress — n8n 워크플로

높음 복잡도 예약75개의 노드 AI👁 33,185회 조회작성자: Jay Emp0

개요

==🔥 Upgrade to V4== We’ve released Version 4 of our AI Powered Blog Automation workflow. We heard your complains and made a complete redesign built for serious content creators.

ChatGPT 5, Inbound Links, Verified Outbound Links,YOAST seo integration, Company profile, higher SEO ranking, banner images using companys mascot, FAQ sections and conclusions, 35% cost reduction,

📝 Read the New Articles published by Content Farming v4

🛒 View the updated and improved v4 workflow

👻 No technical exper

사용된 노드

HTTP RequestMongoDBWordpressCodeHTMLAI AgentOpenAI Chat ModelStructured Output ParserOpenAIText Classifier

워크플로 미리보기

Step 1. Save news in a vector store (runs dai
Step 2: Relevance scoring
Consider improving this by using
- serp api
- jina ai
- [perplexity ai](https://www.perplexity.ai
Steps
1. RSS Feed Ingestion (Daily Trigger)
[x] Fetch latest articles from curated AI RSS feeds:
[x] OpenAI, Meta AI, DeepMind, arXiv AI, HuggingFace, T
[x] Dedupl
Step 3: Research the news articles
Double click to edit me. Guide
Step 4,5,6,7: Write the article and prepare S
Double click to edit me. Guide
Step 8,9: Generate image and create blog arti
modelmodelmodelmodelmodelmodelmodelmodelmodelparserparserparserparserparserparserparser
S
Split Out
G
Get Articles Daily
S
Set Tech News RSS Feeds
R
Read RSS News Feeds
S
Set and Normalize Fields
OpenAI Chat Model
Text Classifier
AI Agent
OpenAI Chat Model1
A
Aggregate
Structured Output Parser
F
Filter
HTTP Request
HTML
OpenAI Chat Model2
AI Agent1
Structured Output Parser1
A
Aggregate1
AI Agent2
OpenAI Chat Model3
Structured Output Parser2
S
Split Out2
S
Split Out1
MongoDB
MongoDB1
MongoDB3
MongoDB4
AI Agent3
OpenAI Chat Model4
Structured Output Parser3
Code3
Code4
MongoDB2
AI Agent5
OpenAI Chat Model6
Code7
MongoDB7
AI Agent6
OpenAI Chat Model7
MongoDB5
Code5
Code
AI Agent7
OpenAI Chat Model8
MongoDB6
Code6
Structured Output Parser4
MongoDB8
OpenAI
AI Agent4
OpenAI Chat Model5
Structured Output Parser5
Wordpress1
Set Image
Upload image2
Set metatag1
Code12
MongoDB15
Wordpress2
MongoDB16
Code14
Code8
HTTP Request1
HTTP Request2
W
Wait
HTTP Request3
G
Get Articles Daily1
G
Get Articles Daily2
G
Get Articles Daily3
Structured Output Parser6
Code9
Transform news to MD
Code1
L
Loop Over Items
Code10
75 nodes70 edges

작동 원리

  1. 1

    트리거

    워크플로는 예약 트리거로 시작합니다, 정해진 일정에 따라 실행.

  2. 2

    처리

    데이터가 75개의 노드를 통해 흐릅니다, connecting agent, aggregate, code.

  3. 3

    출력

    워크플로가 자동화를 완료하고 구성된 대상에 결과를 전달합니다.

노드 세부 정보 (75)

HT

HTTP Request

httpRequest

#1
MO

MongoDB

mongoDb

#2
WO

Wordpress

wordpress

#3
CO

Code

code

#4
HT

HTML

html

#5
AI

AI Agent

n8n-nodes-langchain.agent

#6
OP

OpenAI Chat Model

n8n-nodes-langchain.lmChatOpenAi

#7
ST

Structured Output Parser

n8n-nodes-langchain.outputParserStructured

#8
OP

OpenAI

n8n-nodes-langchain.openAi

#9
TE

Text Classifier

n8n-nodes-langchain.textClassifier

#10

이 워크플로 가져오는 방법

  1. 1오른쪽의 JSON 다운로드 버튼을 클릭하여 워크플로 파일을 저장합니다.
  2. 2n8n 인스턴스를 열고 워크플로 → 새로 만들기 → 파일에서 가져오기로 이동합니다.
  3. 3다운로드된 content-farming-ai-powered-blog-automation-for-wordpress 파일을 선택하고 가져오기를 클릭합니다.
  4. 4각 서비스 노드에 대한 자격 증명(API 키, OAuth 등)을 설정합니다.
  5. 5워크플로 테스트를 클릭하여 모든 것이 작동하는지 확인한 후 활성화합니다.

또는 n8n → JSON에서 가져오기에 직접 붙여넣기:

{ "name": "Content farming - : AI-powered blog automation for WordPress", "nodes": [...], ...}

통합

agentaggregatecodefilterhtmlhttprequestlmchatopenaimongodbopenaioutputparserstructuredrssfeedreadscheduletriggersetsplitinbatchessplitouttextclassifierwaitwordpress

이 워크플로 가져오기

한 번의 클릭으로 다운로드 및 가져오기

JSON 다운로드n8n.io에서 보기
노드75
복잡도high
트리거scheduled
조회수33,185
카테고리AI

제작자

Jay Emp0

Jay Emp0

@jay-emp0

태그

agentaggregatecodefilterhtmlhttprequestlmchatopenaimongodbopenaioutputparserstructured

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