This article provides a complete, practical walkthrough of the Twitter Slack Automation 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:
   Automated Twitter Mention Alerts: How to Monitor Your Brand in Real-Time Using n8n
   
   Meta Description:
   Learn how to use n8n to automate Twitter monitoring and receive real-time Slack alerts for new brand mentions. Improve your brand awareness and social listening workflow instantly.
   
   Keywords:
   n8n workflow, Twitter automation, Slack notifications, brand monitoring, mention alerts, Twitter brand mentions, social media automation, n8n tutorial, social listening, Slack integration
   
   Third-Party APIs Used:
   
   - Twitter API (via Twitter OAuth1 API credentials)
   - Slack API (via Slack Access Token)
   
   Article:
   
   In the age of digital communication, real-time brand monitoring is more important than ever. Whether you're a startup looking to engage early adopters or a large enterprise managing reputation at scale, keeping track of public mentions on social platforms like Twitter is critical. Thankfully, this doesn’t have to be a manual process. With n8n—an extendable workflow automation tool—you can automatically monitor Twitter for mentions of your brand and receive real-time alerts in Slack.
   
   This article explores an n8n workflow that does exactly that: scrapes Twitter mentions of your company (@n8n_io in this case) every 10 minutes and sends relevant tweets directly to a Slack channel. Let’s break the workflow down and understand how it works.
   
   ❶ Workflow Overview
   
   The objective of this workflow, titled "Scrape Twitter for mentions of company", is to fetch the latest 50 mentions on Twitter, filter out the ones posted in the last 10 minutes, and send them to a Slack channel.
   
   The main components include:
   
   - Scheduled execution every 10 minutes
   - Twitter data fetch and timestamp filtering
   - Slack message formatting and notification
   
   ❷ Step-by-Step Breakdown
   
   ▶ Run Every 10 Minutes
   The workflow begins with a Cron node that triggers the entire sequence every 10 minutes. This ensures the workflow is consistently checking for new Twitter mentions within that time window.
   
   ▶ Setup
   Next, the workflow initializes parameters, currently including:
   - Twitter search value: @n8n_io
   - Slack channel: #recent-tweets
   
   This makes the workflow easily configurable for other companies or brands by simply changing these setup values.
   
   ▶ Now - 10 Minutes
   Using the Date & Time node, the workflow calculates the current time minus 10 minutes. This reference timestamp is used to determine which tweets are actually new.
   
   ▶ Get Last 50 Mentions
   Using the Twitter node, the workflow searches Twitter for the latest 50 tweets that mention the brand (based on the Setup node’s configuration). This leverages the Twitter API and requires valid OAuth credentials.
   
   ▶ Created Since Last Run?
   An IF node compares the creation time of each tweet against the previously computed “ten minutes ago” timestamp. Only tweets published in the last 10 minutes pass through to the next stage.
   
   ▶ Filter Tweet Data
   To reduce data noise, a Set node extracts only two values from each tweet:
   - The tweet text
   - A direct URL to the tweet
   
   These pieces of information are then formatted into a clean Slack message.
   
   ▶ Post to Slack
   Finally, using the Slack node and the Slack Access Token, the workflow posts a message to the specified Slack channel for each relevant tweet. The final message appears as:
   
   New Mention!: "Here is the tweet text..."
   See it here: https://twitter.com/username/status/1234567890
   
   This alerts your team instantly when someone tweets about your brand, enabling quick responses, potential engagement, or the opportunity to mitigate any negative feedback in real-time.
   
   ❸ Why Use This Workflow?
   
   Here are a few practical benefits:
   
   - Real-Time Monitoring: Catch new mentions instantly without refreshing Twitter feeds.
   - Team Visibility: Integrate with Slack so your marketing or customer success team is always in the loop.
   - Scalability: Easily modify to track multiple handles or keywords.
   - Autonomy: Once deployed, the system runs without further manual input.
   
   ❹ Customization Ideas
   
   - Track multiple keywords or hashtags.
   - Include tweet author and follower count in your Slack message.
   - Add sentiment analysis using AI APIs before posting to Slack.
   - Send alerts only for tweets above a certain engagement threshold (e.g., likes or retweets > 10).
   
   ❺ Get Started
   
   To replicate this or modify it for your own use:
   1. Install and configure n8n (locally or via cloud).
   2. Authenticate with Twitter and Slack APIs.
   3. Use the workflow structure described above.
   4. Customize search queries and Slack channels as needed.
   
   ❻ Conclusion
   
   This powerful n8n workflow is a practical and scalable solution for proactive brand monitoring. Instead of manually combing through mentions or relying on expensive third-party solutions, you get a low-cost, customizable automation that brings Twitter insights directly to your internal communications.
   
   In an era where timing is everything, automating social listening is not just smart—it’s essential.
   
   —
   
   Want to automate more of your workflows? Explore the n8n documentation and community to see how far you can take your automation journey.
   
   🛠️ APIs Used:
   - Twitter API (via Twitter OAuth integration in n8n)
   - Slack API (via Slack Access Token for the Slack node)
   
   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.