This article provides a complete, practical walkthrough of the Http Schedule 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:  
   Automating AI News Updates to Twitter Using n8n and Perplexity AI
   
   Meta Description:  
   Learn how to automate daily AI news posting to Twitter (X) using n8n, the Perplexity AI API, and scheduled triggers. This guide showcases how low-code automation simplifies content curation.
   
   Keywords:  
   n8n workflow, Perplexity AI API, AI news automation, post to Twitter, X automation, tech news bot, llama-3 online model, daily AI updates, automated social media posts, no-code tools
   
   Third-Party APIs Used:  
   
   - Perplexity AI API (https://api.perplexity.ai)
   - Twitter (X) API via OAuth2
   
   Article:
   
   In today’s fast-paced digital landscape, keeping up with the latest developments in artificial intelligence can be overwhelming—and sharing them efficiently can be even more time-consuming. Enter low-code automation tools like n8n, which enable seamless integrations between content sources and publishing platforms. In this article, we’ll explore an n8n workflow that automates news curation from Perplexity AI and posts a concise update directly to X (formerly Twitter), all with minimal setup and maximum impact.
   
   Overview of the Workflow
   
   The automation—titled “Search news using Perplexity AI and post to X (Twitter)”—is designed to search for the latest news on artificial intelligence every 21 hours and share a single news item to a designated X account. Powered by n8n’s native nodes and Perplexity AI’s advanced language model (LLaMA 3.1 Sonar Online), this workflow ensures timely, objective, and well-formatted updates suitable for a tech-savvy social media audience.
   
   Let’s break it down by its components:
   
   1. Scheduled News Trigger  
   
   The automation begins with a Schedule Trigger node that initiates the workflow approximately every 21 hours. To avoid predictable posting times, the trigger chooses a random minute each cycle using JavaScript logic:
   
   ```javascript
   "triggerAtMinute": "={{Math.floor(Math.random() * 60)}}"
   ```
   
   This ensures the tweets are scattered across different hours of the day, avoiding bot-like behavior.
   
   2. Defining the Search Input
   
   Next, the Set node labeled searchQuery specifies the search term:  
   "What’s the latest news in artificial intelligence?"
   
   This static string can easily be turned dynamic based on recent trends or seasonal keywords, giving users flexibility to tailor the workflow to different topics over time.
   
   3. Injecting Credentials
   
   The set API key node securely injects your Perplexity API key into the workflow. In a production environment, storing credentials securely within n8n’s credential vault is recommended rather than hard-coding them in the workflow JSON.
   
   4. Querying Perplexity AI
   
   This is where the magic happens. The HTTP Request node posts the search query to Perplexity AI’s /chat/completions endpoint. The chosen model, llama-3.1-sonar-small-128k-online, supports online search and can produce up-to-date responses. The payload includes:
   
   - Role configuration: setting the assistant as a “social media assistant”
   - Strict format instructions: single-line tweet with a short headline and a direct link
   - Filters for search recency and domain: returns only news from the past day and limits to perplexity.ai domain
   - Token limit: ensures brevity for tweet compliance
   - Temperature & penalties: optimized for informative, repetitive-safe summaries suitable for publishing
   
   This step effectively transforms an AI chatbot into your 24/7 social media editor.
   
   5. Posting to X (Twitter)
   
   Finally, the Perplexity-generated summary, formatted to meet Twitter’s character limits and best practices, is handed off to the Post to X node. This node uses an authenticated Twitter OAuth2 account prepared in advance. The final message is posted exactly as received, without additional formatting.
   
   A sample tweet output could resemble:
   
   Mastercard launches Agent Pay, allowing AI agents to make purchases for users. https://www.perplexity.ai/page/mastercard-unveils-agent-pay-e-qWXnaUEzQZWCqsxF4l43zA
   
   Workflow Benefits
   
   This automation workflow demonstrates an efficient pipeline from information retrieval to public dissemination, offering valuable benefits:
   
   - Timeliness: News is sourced fresh every 21 hours using real-time search with recency filters.
   - Consistency: Posts are shared regularly without human intervention.
   - Curation: Only one, most relevant news item is published—keeping your feed uncluttered.
   - Editorial Control: The system prompt ensures outputs stay under 200 characters with a clear format, perfect for social platforms like X.
   
   Use Cases and Customization
   
   While this workflow highlights AI news, customizable inputs mean it could work equally well for biotechnology, climate, finance, or even pop culture topics using a suitable query phrase. Changing the posting frequency, source domain filters, or modifying the prompt allows full control over editorial tone and cadence.
   
   Conclusion
   
   This n8n workflow is a shining example of how automation, powered by advanced AI like Perplexity and a flexible workflow tool like n8n, can make social media management both smarter and simpler. Whether you’re a tech blogger, a news curator, or a marketing team looking to keep your followers informed, this setup can save you hours while maintaining quality and relevance.
   
   By combining real-time natural language processing with scheduled task automation, this solution transforms repetitive content creation into an intelligent, autonomous process. Welcome to the future of social media automation.

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.