This article provides a complete, practical walkthrough of the Splitout Code Create Webhook n8n agent. It connects HTTP Request, Webhook across approximately 1 node(s). Expect a Intermediate setup in 15-45 minutes. One‑time purchase: €29.

What This Agent Does

This agent orchestrates a reliable automation between HTTP Request, Webhook, handling triggers, data enrichment, and delivery with guardrails for errors and rate limits.

It streamlines multi‑step processes that would otherwise require manual exports, spreadsheet cleanup, and repeated API requests. By centralizing logic in n8n, it reduces context switching, lowers error rates, and ensures consistent results across teams.

Typical outcomes include faster lead handoffs, automated notifications, accurate data synchronization, and better visibility via execution logs and optional Slack/Email alerts.

How It Works

The workflow uses standard n8n building blocks like Webhook or Schedule triggers, HTTP Request for API calls, and control nodes (IF, Merge, Set) to validate inputs, branch on conditions, and format outputs. Retries and timeouts improve resilience, while credentials keep secrets safe.

Third‑Party Integrations

• HTTP Request
• Webhook

Import and Use in n8n

1. Open n8n and create a new workflow or collection.
2. Choose Import from File or Paste JSON.
3. Paste the JSON below, then click Import.
4. Show n8n JSON

   Title:  
   Automate WordPress Blog Drafts with AI: A Complete n8n Workflow
   
   Meta Description:  
   Discover how to streamline your content creation process by using n8n, OpenAI, and WordPress to automatically generate SEO-friendly blog drafts—including titles, chapters, and images—based on user-submitted keywords.
   
   Keywords:  
   AI blog generation, OpenAI WordPress integration, n8n automation, generate WordPress posts, GPT-4o content creation, DALL·E featured images, automated blog workflow, AI article writing, WordPress draft automation, automated SEO writing
   
   —
   
   Article:
   
   Creating compelling blog content can be time-consuming, especially when you're aiming to publish consistently. With the rapid advances in artificial intelligence and automation, you can now streamline almost every step of your content generation process. In this article, we’ll explore a complete automation workflow built with n8n, OpenAI, and WordPress that takes user-defined keywords and turns them into a fully draft-formatted blog post—complete with structured chapters, SEO-friendly copy, and a custom AI-generated featured image.
   
   Let’s take a look under the hood of this cleverly designed n8n workflow.
   
   User Input and Setup
   
   The process begins with a user form powered by n8n’s formTrigger node. The user is prompted to input:
   
   - A set of topic keywords (comma-separated)
   - Desired number of chapters
   - Maximum word count for the article
   
   Once the form is submitted, the data is captured and passed through a settings node which normalizes values and prepares them for later steps in the workflow.
   
   Generating the Article Structure with OpenAI
   
   The next step uses OpenAI's GPT-4o-mini model via a LangChain-enabled OpenAI node. This node creates the entire skeleton of the blog post:
   
   - SEO-friendly article title
   - A succinct subtitle
   - An introductory paragraph
   - A list of logically ordered chapters with titles and individual prompts
   - A concluding paragraph
   - An image prompt specifically crafted for relevant cover art
   
   To ensure informative and reliable content, this node is integrated with Wikipedia through LangChain’s Wikipedia tool, allowing GPT-4o to verify and enrich the article with accurate data.
   
   Verifying Data Quality
   
   Before diving into article generation, the workflow performs a rigorous quality check using the If node in n8n. It validates that all critical data fields—title, subtitle, intro, conclusion, image prompt, and a non-empty list of chapters—are not only present but meaningful. If there's an issue, the user is alerted to retry, avoiding the propagation of incomplete content.
   
   Chapter-Based Text Generation
   
   Each chapter prompt is sent individually to OpenAI’s GPT-4o using a splitOut node, followed by parallel chapter creation. This piece is especially impressive due to its contextual awareness:
   
   - If applicable, each chapter considers the contents of the prior and subsequent chapters, maintaining logical flow.
   - Chapters avoid redundancy, aiming for depth and cohesion.
   
   All textual output is formatted in HTML—with basic tags like <strong> and <em>—to ensure compatibility with WordPress editing standards.
   
   Merging and Final Content Preparation
   
   A merge node brings together the chapter titles and their respective generated texts, which are then fed into a Code node to assemble the final article. The flow includes:
   
   - The introduction
   - Chapter-wise content with headings
   - A unified conclusions section
   
   The result is a polished body of text ready for publishing.
   
   Draft Creation in WordPress
   
   Next, the article is posted as a draft in WordPress using the native WordPress API node in n8n. At this point, it exists as an unpublished blog post awaiting review or scheduling.
   
   Creating a Featured Image with DALL·E
   
   What’s a good blog post without a striking cover image? The generated image prompt is passed to DALL·E via OpenAI’s image endpoint to create a high-resolution, realistic photo-style image (1792x1024 px). Parameters ensure natural style aesthetics, such as simulating a photography output from a Sigma 85mm f/1.4 lens.
   
   Uploading and Assigning the Image
   
   The image is then posted to WordPress’s media library through an HTTP request node. After uploading, its media ID is captured and sent alongside the blog post to update the draft with the correct featured image using another HTTP PATCH request.
   
   User Feedback
   
   The final stretch of the workflow provides user feedback. Upon successful post-drafting and media assignment, the user is notified with a success message showing that the article was created as a draft. If anything goes wrong before this phase, a fallback message invites the user to refresh and retry.
   
   Why This Matters
   
   This workflow showcases the full potential of n8n as a true low-code automation powerhouse, especially when combined with AI tools and CMS platforms like WordPress. It eliminates the friction of writing, formatting, illustrating, and reviewing basic content drafts—empowering creators to focus on refinement and publishing.
   
   Whether you manage a content agency, personal blog, or digital marketing team, this setup provides a scalable solution to generate informative, consistent, and ready-to-publish drafts tailored to your brand’s needs.
   
   Third-Party APIs and Tools Used
   
   Here’s a list of all the third-party tools integrated in this workflow:
   
   1. OpenAI (GPT-4o-mini via LangChain) – Used for content generation and DALL·E image creation
   2. Wikipedia (via LangChain Tool) – Used to ensure factual accuracy in the generated content
   3. WordPress REST API – Used for posting drafts and uploading media
   4. n8n HTTP Request Node – Used for setting WordPress featured image metadata
   5. n8n Form Trigger – Serves as the frontend for user input
   
   Conclusion
   
   By combining automation with artificial intelligence and powerful APIs, this n8n workflow enables creators to produce rich, SEO-friendly WordPress drafts within minutes. The streamlined process—from form submission to final article draft with visuals—illustrates how modern no-code tools can radically improve productivity in content marketing.
   
   If you’re looking to automate your editorial pipeline or simply want a faster way to develop initial drafts, this AI-driven WordPress generator might just be your next secret weapon.

5. Set credentials for each API node (keys, OAuth) in Credentials.
6. Run a test via Execute Workflow. Inspect Run Data, then adjust parameters.
7. Enable the workflow to run on schedule, webhook, or triggers as configured.

Tips: keep secrets in credentials, add retries and timeouts on HTTP nodes, implement error notifications, and paginate large API fetches.

Validation: use IF/Code nodes to sanitize inputs and guard against empty payloads.

Why Automate This with AI Agents

AI‑assisted automations offload repetitive, error‑prone tasks to a predictable workflow. Instead of manual copy‑paste and ad‑hoc scripts, your team gets a governed pipeline with versioned state, auditability, and observable runs.

n8n’s node graph makes data flow transparent while AI‑powered enrichment (classification, extraction, summarization) boosts throughput and consistency. Teams reclaim time, reduce operational costs, and standardize best practices without sacrificing flexibility.

Compared to one‑off integrations, an AI agent is easier to extend: swap APIs, add filters, or bolt on notifications without rewriting everything. You get reliability, control, and a faster path from idea to production.

Best Practices

• Credentials: restrict scopes and rotate tokens regularly.
• Resilience: configure retries, timeouts, and backoff for API nodes.
• Data Quality: validate inputs; normalize fields early to reduce downstream branching.
• Performance: batch records and paginate for large datasets.
• Observability: add failure alerts (Email/Slack) and persistent logs for auditing.
• Security: avoid sensitive data in logs; use environment variables and n8n credentials.

FAQs

Can I swap integrations later? Yes. Replace or add nodes and re‑map fields without rebuilding the whole flow.

How do I monitor failures? Use Execution logs and add notifications on the Error Trigger path.

Does it scale? Use queues, batching, and sub‑workflows to split responsibilities and control load.

Is my data safe? Keep secrets in Credentials, restrict token scopes, and review access logs.