This article provides a complete, practical walkthrough of the Manual Twitter Automate Scheduled 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 Twitter Mentions Alerts to Rocket.Chat Using n8n
   
   Meta Description:
   Learn how to use n8n to create an automated workflow that monitors Twitter for @n8n_io mentions and sends notifications to Rocket.Chat. Discover how the integration works and how to set it up in minutes.
   
   Keywords:
   n8n workflow, Twitter API, Rocket.Chat integration, Twitter mentions alert, Twitter automation, social media monitoring, n8n tutorial, chat notifications, workflow automation, real-time Twitter alerts
   
   Third-Party APIs Used:
   
   1. Twitter API (OAuth1) – used to search for mentions of @n8n_io.
   2. Rocket.Chat API – used to send automated messages to a chat channel.
   
   Article:
   
   Streamlining Social Media Monitoring: How to Automatically Alert Rocket.Chat When Someone Mentions @n8n_io on Twitter
   
   In the era of real-time communication and rapid feedback loops, staying updated on social mentions of your brand is not just helpful—it’s essential. But rather than manually monitoring Twitter for every mention of your handle, wouldn’t it be more efficient to automate that process? Enter n8n—an open-source workflow automation tool that allows you to connect APIs, transform data, and build powerful automation workflows without writing complex backend code.
   
   In this article, we’ll explore an elegant n8n workflow that listens for mentions of @n8n_io on Twitter and sends real-time messages to a Rocket.Chat channel whenever a new tweet pops up. Let’s break down how this works.
   
   The Goal: Watch Twitter, Notify Rocket.Chat
   
   The purpose of this workflow is straightforward: stay informed whenever someone tweets about @n8n_io. With this automation in place, team members leveraging Rocket.Chat won’t need to scroll Twitter or ping alert bots—new mentions will simply appear in the general chat channel, ready for immediate viewing and response.
   
   How the Workflow is Designed
   
   This n8n workflow includes six primary nodes that work together to track and act on Twitter mentions:
   
   1. Cron Trigger (Checks Every Minute)
   The workflow starts with a Cron node, set to trigger every minute. This creates a time-based automation that initiates the entire flow without manual intervention. No need to rely on a user clicking an “execute” button—the automation runs itself every 60 seconds.
   
   2. Twitter Node (Search for Mentions)
   Triggered by the cron job, the Twitter node conducts a search for the term “@n8n_io”. This node is configured using Twitter’s API and requires OAuth1 credentials. It retrieves the latest public mentions of the handle and sends the corresponding tweet data downstream.
   
   3. Set Node (Filter Tweet Data)
   Because Twitter's API can return a large volume of information per tweet, we use a Set node to cleanly extract only the essential details:
   
   - Tweet text
   - Tweet ID
   - URL to the tweet, constructed using the tweet’s user screen name and ID string
   
   By filtering out unnecessary data, we streamline the logic and make the next steps easier to manage.
   
   4. Function Node (Filter for New Mentions Only)
   This is one of the smartest parts of the workflow. With each cron execution, the Twitter node may return duplicate tweets from previous runs. To prevent repeated alerts, a Function node compares the current tweet IDs with those stored in the workflow’s static data.
   
   If a tweet ID was not previously encountered, it’s considered new and passed to the next node. Otherwise, it’s ignored. The node also updates the static memory with new IDs to maintain an evolving history of what’s already been seen.
   
   5. Rocket.Chat Node (Send Chat Alert)
   Finally, the Rocket.Chat node crafts a message with the tweet’s content and a clickable URL, pushing it into the “general” channel. With a simple notification like:
   
   New Mention!: [Tweet text]  
   See it here: [Tweet URL]
   
   your team gets real-time visibility into your social footprint—without leaving Rocket.Chat.
   
   You can even customize this alert with additional formatting like Markdown, emojis, or tags to increase visibility.
   
   6. Manual Trigger (Optional Debugging)
   There is also a Manual Trigger node included in the workflow, but it’s disabled by default. It’s useful for testing or debugging each part of the workflow during setup but is not required once the automation is fully operational.
   
   How to Make It Your Own
   
   While this example focuses on mentions of @n8n_io, you can adapt it to any Twitter handle or specific keyword. Want to monitor your company hashtag, or a competitor’s customer feedback? Just update the search term in the Twitter node.
   
   Additionally, you can change the Rocket.Chat channel, add formatting to the alerts, or even forward those tweets to additional services like Slack, email, or Microsoft Teams—all within n8n.
   
   Why This Automation Matters
   
   - Stay informed in real-time
   - Improve social responsiveness
   - Centralize alerts in chat where your team already works
   - Minimize redundant notifications with smart tweet filtering
   - Leverage free and open-source tools
   
   Conclusion
   
   With n8n’s highly customizable workflow engine, you can easily monitor your digital presence and ensure your team never misses an @mention again. In just a few simple nodes, you’ve created an always-on social monitor and alert system that bridges Twitter and Rocket.Chat.
   
   Whether you're a community manager, marketing lead, or developer advocate, this automation can save you time and keep your team well-informed. And best of all, it’s built with tools you control.
   
   Explore more powerful, code-lite automations with n8n, and let your systems talk to each other just like you imagined.
   
   Happy automating!

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.