This article provides a complete, practical walkthrough of the Manual Splitout Automation 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:  
   Automating GitHub Trending Scrapes with n8n: A Workflow to Track the Top 13 Repositories
   
   Meta Description:  
   Learn how to build a no-code automation workflow using n8n to scrape GitHub Trending and extract the top 13 repositories, including details like repository name, author, description, and language.
   
   Keywords:  
   n8n, GitHub Trending, web scraping, no-code automation, GitHub repo tracker, HTML scraping, GitHub API, data extraction, top GitHub repositories, open-source automation
   
   Third-Party APIs Used:  
   - GitHub Trending (https://github.com/trending) – Public web page (not an official API)
   
   —
   
   Article:
   
   Tracking GitHub's Daily Trending Repositories with n8n Automation
   
   In the fast-paced world of open-source development, keeping up with the latest trends on GitHub is crucial for developers, tech enthusiasts, and product teams. But manually checking the GitHub Trending page every day is inefficient and time-consuming. Enter n8n — the powerful, open-source, no-code/low-code workflow automation tool — which can automate the data collection process entirely.
   
   This article explains how to create an n8n workflow that scrapes GitHub's trending page and extracts data from the top 13 repositories of the day. The workflow automates fetching, processing, and formatting this data for easy use in other automation or reporting pipelines.
   
   Overview of the Workflow
   
   The “Scrape Today’s GitHub Trend 13 Top Repositories” workflow is built around capturing real-time data from GitHub’s public Trending page. Let’s break down how it works, step-by-step.
   
   1. Manual Trigger
   
   The workflow starts with the n8n Manual Trigger node. This allows users to run the workflow interactively from the n8n editor by clicking the ‘Test workflow’ button. This setup is optimal for development and testing but can easily be swapped for a Cron Trigger for daily automation.
   
   2. Fetching the GitHub Trending Page
   
   Next, an HTTP Request node makes a GET call to:
   https://github.com/trending
   
   Although GitHub doesn’t provide an official API for viewing trending repositories, its Trending page contains all necessary data embedded in its HTML.
   
   3. Extracting the Repository Container
   
   Using the HTML Extract node (named "Extract Box"), the workflow targets the `div.Box` element on the page, which contains all trending repositories. This isolates a large block of HTML we need to dig deeper into.
   
   4. Pulling Out Each Repository
   
   Another HTML Extract node (called "Extract all repositories") targets `article.Box-row`, which wraps individual repository data on the GitHub Trending page. It extracts an array, with each entry representing a unique repository in HTML format.
   
   5. Splitting the Data into Items
   
   Because n8n works best with one item per execution path, the SplitOut node converts the array of repositories into individual items so each one can be processed independently.
   
   6. Extracting Useful Metadata
   
   For each repository, another HTML Extract node is used (called "Extract repository data") to parse out meaningful data points, including:
   
   - repository name and author via the `a.Link` selector
   - primary language via the `span.d-inline-block` tag
   - description from the `p` tag
   
   7. Setting Output Variables
   
   Finally, the Set node extracts and reformats the parsed data for each repository:
   
   - Splits the repository full name (e.g., "vercel/next.js") into author and title
   - Constructs a direct URL: https://github.com/vercel/next.js
   - Records the description and detected programming language
   - Adds a timestamp for when the data was scraped
   
   The output for each repository now includes:
   - Repository
   - Author
   - Title
   - Description
   - Language
   - URL
   - Timestamp
   
   Potential Applications
   
   This n8n workflow can be extended or modified for a wide range of uses:
   
   - Automatically email or Slack a daily digest of trending repositories
   - Add entries to an Airtable or Notion database for trend analysis
   - Build a personal dashboard displaying trending GitHub projects
   - Trigger further automations such as opening issues, cloning repos, or sending alerts
   
   Why Use n8n for This?
   
   Unlike using custom scripts or scraping libraries like BeautifulSoup or Puppeteer, n8n allows you to visually build and monitor your workflow in a modular way — no advanced programming required. Its built-in nodes for HTTP requests and HTML extraction make it particularly powerful for web scraping and automation of online content.
   
   And since n8n is self-hostable and open-source, you stay in full control of your data and usage patterns — a significant benefit over SaaS tools with rate limits or restricted access.
   
   Final Thoughts
   
   Scraping GitHub’s Trending repositories with n8n opens up exciting possibilities for developers and data trackers. With this workflow, you can automate insights into what’s gaining traction in the coding community — whether you're tracking specific languages, looking for potential collaborators, or scouting for product inspiration.
   
   As the no-code movement continues to grow, tools like n8n empower users to create complex workflows with simplicity and greater accessibility. And this GitHub scraping example is just the tip of the iceberg.
   
   Want to try it yourself? Head over to n8n.io and start automating the way you monitor GitHub trends.
   
   —  
   End of Article

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.