Perplexity to GitHub, SEO posts published reliably
Publishing longform SEO content sounds simple until you’re doing it every week. Topic research, source checking, outline creation, drafting, formatting, file naming, pushing to GitHub. Then you notice the “quick post” took your whole afternoon.
This hits marketing leads first, because consistency drives traffic. But agency owners shipping content for clients and founders building a content moat feel it too. With Perplexity GitHub automation, you stop babysitting the pipeline and start getting publish-ready files on schedule.
Below, you’ll see exactly how this workflow turns trending research into a 2,000+ word article, formats it as blog-ready JSON, and commits it to your repository every 8 hours.
How This Automation Works
See how this solves the problem:
n8n Workflow Template: Perplexity to GitHub, SEO posts published reliably
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n1["<div style='background:#f5f5f5;padding:10px;border-radius:8px;display:inline-block;border:1px solid #e0e0e0'><img src='https://flowpast.com/wp-content/uploads/n8n-workflow-icons/perplexity.dark.svg' width='40' height='40' /></div><br/>Deep Research"]
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n3["<div style='background:#f5f5f5;padding:10px;border-radius:8px;display:inline-block;border:1px solid #e0e0e0'><img src='https://flowpast.com/wp-content/uploads/n8n-workflow-icons/github.dark.svg' width='40' height='40' /></div><br/>Create File in GitHub"]
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n5["<div style='background:#f5f5f5;padding:10px;border-radius:8px;display:inline-block;border:1px solid #e0e0e0'><img src='https://flowpast.com/wp-content/uploads/n8n-workflow-icons/perplexity.dark.svg' width='40' height='40' /></div><br/>Find Trending Topics"]
n6["<div style='background:#f5f5f5;padding:10px;border-radius:8px;display:inline-block;border:1px solid #e0e0e0'><img src='https://flowpast.com/wp-content/uploads/n8n-workflow-icons/openAi.dark.svg' width='40' height='40' /></div><br/>Generate 2000+ Word Article"]
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The Challenge: Consistent SEO publishing without the busywork
If you want SEO results, you need volume and consistency. The problem is that “writing a post” isn’t one task. It’s ten. You research what’s trending, skim sources, pull stats, write, rewrite, format headings, create metadata, generate a slug, estimate reading time, then push everything to GitHub or your CMS. Miss one small step and you get broken layouts, duplicate filenames, or an article that looks fine in Google Docs but fails in production.
It adds up fast. Here’s where it usually breaks down once you try to scale beyond the occasional post.
- Topic research becomes a recurring meeting instead of a repeatable system.
- Formatting and metadata turn into copy-paste work that quietly introduces errors.
- Writers end up starting from a blank page, even when the same structure would work every time.
- Publishing to GitHub is “easy” until filenames, paths, and JSON rules need to be perfect.
The Fix: Perplexity research → OpenAI draft → GitHub publish
This workflow runs on a schedule (every 8 hours by default) and behaves like a lightweight editorial pipeline you don’t have to manage. It starts by pulling trending subjects via Perplexity, then assigns topic details so each run has a clear theme to research. Next, Perplexity performs deeper “in-depth research,” which gives your content real material to work with instead of generic filler. OpenAI then turns that research into a longform, SEO-friendly post designed to be comprehensive (2,000+ words). Finally, the workflow structures everything into blog-ready JSON (including metadata like slug and reading time) and commits the file into your GitHub repo in the correct path.
The workflow starts on a timed trigger, so you never have to remember to run it. From there, Perplexity handles discovery and research, OpenAI creates the longform draft, and a formatting step converts it into clean JSON. GitHub receives a ready-to-publish content file without manual uploading.
What Changes: Before vs. After
| What This Eliminates | Impact You’ll See |
|---|---|
|
|
Real-World Impact
Say you publish 1 longform article per day. Manually, trending research (about 30 minutes), deeper research and sourcing (about 45 minutes), drafting (about 2 hours), and formatting + GitHub commit (about 20 minutes) puts you around 3.5 hours per post. With this workflow, you spend maybe 10 minutes picking categories and reviewing the output, then the scheduled run generates the draft and commits the JSON for you. That’s roughly 3 hours back each day, and your publishing cadence stops depending on someone’s calendar.
Requirements
- n8n instance (try n8n Cloud free)
- Self-hosting option if you prefer (Hostinger works well)
- Perplexity to retrieve trending topics and research.
- OpenAI to generate the longform SEO article.
- GitHub to store published JSON content files.
- Perplexity API key (get it from your Perplexity account dashboard)
- OpenAI API key (get it from the OpenAI dashboard)
Skill level: Intermediate. You’ll be connecting API credentials and confirming your repo path and file naming rules.
Need help implementing this? Talk to an automation expert (free 15-minute consultation).
The Workflow Flow
A scheduled trigger fires every 8 hours. You can keep that cadence, or change it to daily, weekdays only, or whatever matches your editorial plan.
Perplexity retrieves trending subjects, then runs deeper research. The first pass is about discovering what’s hot in your chosen categories. The second pass focuses on substance: stats, perspectives, and the kind of context that makes a longform post feel credible.
OpenAI generates the longform article from the research. Instead of “write a blog post about X,” the model is working from a research payload, which usually means fewer empty paragraphs and less repetition. Honestly, this is where most AI content workflows fall apart, and it’s why the research stage matters.
The content is structured into blog-ready JSON and pushed to GitHub. A formatting step builds fields like slug, keywords, and reading time, then the GitHub node publishes the file to your chosen folder (the workflow’s default is a blog-data style directory).
You can easily modify the topic categories to match your niche, or change the output JSON shape to match your blog platform. See the full implementation guide below for customization options.
Step-by-Step Implementation Guide
Step 1: Configure the Scheduled Cycle Trigger
Set the workflow’s schedule so the pipeline runs automatically.
- Add and open Scheduled Cycle Trigger.
- Configure the schedule to match your publishing cadence (daily/weekly/etc.).
- Confirm that Scheduled Cycle Trigger connects to Retrieve Trending Subjects.
Step 2: Connect Perplexity for Topic Discovery
Use Perplexity to find trending subjects and gather deep research context.
- Open Retrieve Trending Subjects and set your query or prompt to pull current topics.
- Credential Required: Connect your Perplexity credentials (this node has no credentials configured).
- Open Assign Topic Details and map any fields needed from the trending subject output.
- Open In-Depth Research and set the research prompt to use the selected topic.
- Credential Required: Connect your Perplexity credentials for In-Depth Research (this node has no credentials configured).
Step 3: Set Up Generate Longform Article (AI)
Generate a full-length article using the research output.
- Open Generate Longform Article and configure your prompt to consume the research content from In-Depth Research.
- Credential Required: Connect your OpenAI credentials for Generate Longform Article (this node has no credentials configured).
- Confirm the execution flow: In-Depth Research → Generate Longform Article.
Step 4: Configure Output Formatting and GitHub Publishing
Convert the article into structured JSON and publish it to your repository.
- Open Structure Blog JSON and write the code needed to build the final JSON payload from the AI output.
- Open Publish File to GitHub and configure repository, file path, and commit details.
- Credential Required: Connect your GitHub credentials for Publish File to GitHub (this node has no credentials configured).
- Confirm the execution flow: Generate Longform Article → Structure Blog JSON → Publish File to GitHub.
⚠️ Common Pitfall: If Structure Blog JSON doesn’t output valid JSON, Publish File to GitHub may fail or create malformed files. Validate the JSON structure before publishing.
Step 5: Test and Activate Your Workflow
Validate the workflow end-to-end and enable scheduled runs.
- Click Execute Workflow to run from Scheduled Cycle Trigger.
- Verify that Retrieve Trending Subjects produces a topic, and that Generate Longform Article returns longform content.
- Confirm Publish File to GitHub creates or updates the expected file in your repository.
- Turn on Active to enable the scheduled automation in production.
Watch Out For
- GitHub credentials can expire or need specific permissions. If things break, check your GitHub OAuth connection inside n8n credentials and confirm the repo has write access first.
- If you’re using Wait nodes or external rendering, processing times vary. Bump up the wait duration if downstream nodes fail on empty responses.
- Default prompts in AI nodes are generic. Add your brand voice early or you’ll be editing outputs forever.
Common Questions
About 30 minutes if your APIs and repo are ready.
Yes, but someone should be comfortable connecting API keys and testing a run. You won’t write code, though you may tweak prompts and a repo path.
Yes. n8n has a free self-hosted option and a free trial on n8n Cloud. Cloud plans start at $20/month for higher volume. You’ll also need to factor in Perplexity and OpenAI API usage, which depends on article length and how often you run the schedule.
Two options: n8n Cloud (managed, easiest setup) or self-hosting on a VPS. For self-hosting, Hostinger VPS is affordable and handles n8n well. Self-hosting gives you unlimited executions but requires basic server management.
You can adjust the topic categories in the “Retrieve Trending Subjects” step, then tighten the voice and structure in “Generate Longform Article” so it matches your editorial style. If your site doesn’t use JSON, swap the “Structure Blog JSON” formatting so it outputs Markdown files instead. Common tweaks include changing the schedule from every 8 hours to daily, setting stricter keyword rules, and altering the GitHub folder path to match your build pipeline.
Most of the time it’s an auth or permission issue: the token/OAuth app no longer has access to the repo, or the repo owner changed. Reconnect the GitHub credential in n8n, confirm the workflow is pointing to the correct owner/repository, and verify the target path exists. If you’re generating lots of files, you can also hit rate limits, so spacing runs out (or batching commits) helps.
It scales mainly with how many scheduled runs you choose and how much your APIs can handle. On self-hosted n8n, there’s no execution cap (your server resources become the limit), so running every 8 hours is usually easy. If you run it hourly, watch API costs and GitHub commit volume. For most small teams, the bottleneck is review time, not generation.
Often, yes. n8n is better when you want multi-step logic (research → generate → format → commit), predictable scheduling, and a self-hosted option for unlimited runs. Zapier and Make can work, but longform content generation tends to become expensive or awkward once you need branching, validation, and structured file output. GitHub publishing is also more natural in n8n because you can control paths and payloads tightly. If your automation is just “send a draft somewhere,” those tools may feel simpler. Talk to an automation expert if you want a quick recommendation for your exact setup.
Once this is running, your content engine stops relying on “finding time to write.” You get consistent, research-driven posts committed to GitHub, ready for review or deployment.
Need Help Setting This Up?
Our automation experts can build and customize this workflow for your specific needs. Free 15-minute consultation—no commitment required.
