This article provides a complete, practical walkthrough of the Splitout Code Import Triggered 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:  
   Streamlining Facebook Engagement: How to Fetch Post Comments Automatically Using n8n
   
   Meta Description:  
   Discover how to automate the retrieval of comments from your Facebook page posts using n8n and the Facebook Graph API. Learn how this workflow simplifies social media data collection for analysis and reporting.
   
   Keywords:  
   n8n, Facebook comments automation, Facebook Graph API, workflow automation, fetch Facebook post comments, social media automation, no-code automation tools, data extraction from Facebook, n8n Facebook workflow, Facebook API integration
   
   Third-Party APIs Used:
   
   - Facebook Graph API
   
   —
   
   Article:  
   Streamlining Facebook Engagement: How to Fetch Post Comments Automatically Using n8n
   
   Managing audience engagement on Facebook can be a daunting task—especially when dealing with multiple posts and an influx of comments on a daily basis. This is where automation tools like n8n come into play, empowering users to centralize operations and streamline the otherwise manual effort of fetching post comments from Facebook.
   
   In this article, we’ll explore a powerful n8n workflow designed specifically to retrieve comments from recent posts on a Facebook page using the Facebook Graph API. Whether you're a digital marketer, community manager, or data analyst, this automation will save you hours of work and unlock actionable insights from customer interactions.
   
   🛠️ The Purpose of the Workflow  
   This workflow fetches the latest posts from a specified Facebook Page and collects comments on each post—filtering, organizing, and structuring them for downstream use such as reporting, data storage, or sentiment analysis.
   
   📥 Workflow Breakdown
   
   Let’s walk through the key components and logic used in this workflow:
   
   1. Manual Trigger for Testing  
   The workflow starts with the Manual Trigger node. This allows the workflow to be tested directly in n8n before activating it in production.
   
   2. Set Facebook Page ID and Desired Number of Posts  
   Next, a Set node captures two important inputs:
   - FB_Page_Id: The ID of the Facebook Page to target.
   - Number_of_Latest_Posts: Defines how many recent posts should be analyzed (in this case, 10).
   
   This makes the workflow dynamic and reusable for different pages and data needs.
   
   3. Retrieve Facebook Posts Using Graph API  
   The "Facebook Graph API: Get Post from Page" node takes the Page ID and pulls a list of recent posts from the /feed endpoint. This is the first use of a third-party service—Facebook’s Graph API, version 20.0.
   
   4. Split Posts Into Individual Items  
   With the "Split Out Posts" node, the retrieved array of post data is broken down into individual records, allowing the workflow to process each post sequentially.
   
   5. Retrieve Comments for Each Post  
   Then, each post ID is fed into another Graph API node titled "Facebook: Get Each Post Comments." This fetches details such as:
   - Comment ID
   - Author name
   - Message text
   - Creation time
   
   Comments are fetched in reverse chronological order.
   
   6. Merge Post and Associated Comments  
   To maintain context, each post is paired with its corresponding comments using the “Merge Post & Comments” node. Since Facebook’s comments may not map 1:1 with posts (or may be missing entirely), a custom code node (“Reverse Item to Match Another Branch”) reverses the order of items so positions match up when combining them.
   
   7. Filter Out Posts with No Comments  
   The merging is followed by a filter node—“Filter Out Null Comments”—which ensures that only posts with actual comments are processed further. This avoids clutter and makes the output more meaningful.
   
   8. Split Comments for Individual Processing  
   The filtered records are passed through a “Split Out Comments” node to handle each comment separately. This makes it possible to extract individual comment metadata and analyze them granularly.
   
   9. Extract Key Fields into Structured Output  
   The final “Select Result Field” node formats the output, capturing important fields such as:
   - Post ID
   - Post creation timestamp
   - Post message content
   - Comment ID
   - Comment datetime
   - Comment message
   - Comment author name
   
   This structured data can then be piped into further automations such as exporting to Google Sheets, sending Slack notifications, or visualizing feedback in a dashboard.
   
   📊 Why Use This Workflow?
   
   - Saves time on manual comment scraping
   - Enables fast response to audience feedback
   - Centralizes comment data for analytics or reporting
   - Easily modifiable and scalable for other social pages
   
   📡 API Authentication and Configuration  
   This n8n workflow requires a valid Facebook Graph API credential. Ensure you have appropriate page-level permissions (usually manage_pages or read_insights) because the API will only return posts and comments if you have the required authorization.
   
   ⚙️ Customization Options  
   You can further extend this workflow by:
   - Adding sentiment analysis on comment text.
   - Automatically tagging or labeling comments.
   - Triggering alerts for comments that match certain keywords or conditions (e.g., complaints, praise, or questions).
   
   🌐 Final Thoughts
   
   This “Get Comments from Facebook Page” workflow harnesses the power of n8n's visual workflow environment and Facebook’s Graph API to automate a repetitive but crucial process in social media management. By turning your Facebook page into a structured data feed, you gain the power to listen, analyze, and respond at scale.
   
   Whether you're tracking engagement, preparing performance reports, or conducting customer research—this workflow unlocks a powerful layer of efficiency and insight. All with no-code or low-code effort.
   
   Give it a try in your automation toolbox, and you’ll never fetch Facebook comments manually again.
   
   —
   
   Need help deploying or customizing this workflow for your use case? Drop your questions below or check out the n8n documentation for advanced scripting and integrations.

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.