This article provides a complete, practical walkthrough of the Datetime Splitout Process n8n agent. It connects HTTP Request, Webhook across approximately 1 node(s). Expect a Simple setup in 5-15 minutes. One‑time purchase: €9.

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 DMARC Report Parsing and Compliance Monitoring with n8n
   
   Meta Description:  
   Discover how to build a workflow in n8n for automating the ingestion, parsing, and evaluation of DMARC XML reports. Learn how this system can store results in a database and send alerts on SPF/DKIM failures.
   
   Keywords:  
   DMARC, DKIM, SPF, n8n workflow, email automation, XML parsing, IMAP, MySQL, Slack notifications, email security, DevOps, compliance
   
   Third-Party APIs and Services Used:  
   - IMAP (Email Trigger)  
   - MySQL Database (Storage of parsed data)  
   - Slack (for notifications via Slack channel)  
   - EmailSend (for sending notification emails)
   
   —
   
   Article:
   
   Streamlining DMARC Parsing and Email Security Notifications Using n8n
   
   With email security being a foremost concern in today’s digital communications, monitoring DMARC (Domain-based Message Authentication, Reporting & Conformance) reports has become an essential DevOps task. These reports help domain owners ensure that emails sent from their domains are properly authenticated using SPF and DKIM standards, and they alert administrators when potentially spoofed or phished messages fail to meet those standards.
   
   Manually parsing DMARC reports—which are delivered as zipped XML files to a domain’s postmaster address—is labor-intensive and error-prone. Fortunately, with low-code automation tools like n8n, this process can be fully automated. In this article, we walk through an n8n workflow that streamlines the ingestion, parsing, evaluation, and storage of DMARC reports, and alerts teams if any SPF or DKIM issues are detected.
   
   How It Works
   
   The n8n workflow named "Parse DMARC reports" is designed to:
   
   1. Monitor a designated email inbox for incoming DMARC reports.
   2. Automatically unzip and parse XML attachments.
   3. Convert parsed data into structured JSON.
   4. Normalize and transform the data into a format suitable for database ingestion.
   5. Insert the parsed data into a MySQL database.
   6. Send notifications via Slack or email if any authentication failures are found.
   
   Let’s examine each of these steps in more detail.
   
   Step 1: Monitoring Email for DMARC Reports
   
   The process begins with the "Email Trigger (IMAP)" node. This node connects to an IMAP-compatible mailbox (typically postmaster@yourdomain.com) and watches for incoming emails that contain DMARC reports. It downloads email attachments upon arrival—specifically, compressed XML reports.
   
   Step 2: Unpacking and Parsing the XML
   
   The workflow includes an "Unzip File" node to open the compressed report followed by the "Extract XML data" and "Parse XML data to JSON" nodes, which convert the raw XML content into structured JSON that can be interpreted by subsequent nodes for data mapping and storage.
   
   Step 3: Handling Multiple Report Entries
   
   DMARC reports can contain multiple records. To accommodate this, the workflow features branching logic using a conditional "If multiple records to parse" node and a "Split Out For Separate Entries" node, which separates each record into individual items for further processing.
   
   Step 4: Formatting Data for Storage
   
   Before inserting into a database, the workflow transforms and organizes the necessary fields:
   - The "Rename column for consistency" and "Map fields for DB input and parse" nodes extract key data like organizational metadata, IP addresses, mail counts, SPF/DKIM evaluation outcomes, and more.
   - Date fields are formatted using the "Begin format date" and "End date format" nodes to ensure compatibility with MySQL standards (formatted as yyyy-MM-dd hh:mm:ss).
   
   Step 5: Storing in MySQL
   
   Now formatted and structured, the data is submitted to a preconfigured MySQL table using the "Input into database" node. Each DMARC record is stored with full detail, enabling analytics, auditing, or compliance reporting.
   
   Step 6: Alerting on Failures
   
   One of the most critical features of this workflow is the automatic notification system. The "If issue with DKIM or SPF" node checks if either SPF or DKIM failed during evaluation. If a failure is detected:
   - A Slack notification is optionally triggered using the "Slack Post Message On Channel" node (currently disabled but easy to enable).
   - Alternatively, an email alert can be sent via the "Send Error Notification Email" node (also available but disabled in the current configuration).
   
   These alerts ensure that your DevOps or security teams are immediately informed of potential spoofing, allowing rapid action to be taken.
   
   Setup Checklist
   
   Before deploying this workflow, ensure the following:
   - An email account (with IMAP access) set up to receive DMARC reports.
   - A correctly configured MySQL or MariaDB database with a designated "dmarc" table.
   - Slack credentials and a selected Slack channel (if Slack notifications are to be used).
   - n8n properly connected to your SMTP for email alerts (if using email notifications).
   
   Conclusion
   
   This n8n workflow provides a powerful automated solution to a normally tedious process—parsing and monitoring DMARC reports for email authentication failures. With robust support for attachment parsing, XML translation, conditional logic, and third-party API integration, this workflow saves time and ensures that critical SPF and DKIM issues are never overlooked. For DevOps engineers, this is a must-have in the security automation toolkit.
   
   By adopting automation tools like n8n, you not only improve reaction time to threats but also enforce email compliance best practices efficiently and at scale.

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.