This article provides a complete, practical walkthrough of the Mondaycom Splitout 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:
   How to Create a Complete Monday.com Item Data Export Workflow Using n8n
   
   Meta Description:
   Learn how to build a powerful n8n workflow for Monday.com that extracts full item data—including subitems and relations—into a unified JSON output for data syncing, reporting, or automation needs.
   
   Keywords:
   n8n workflow, Monday.com API, automation, get Monday item, subitems, board relations, linked pulses, JSON export, data integration, no-code tools
   
   Third-Party APIs Used:
   - Monday.com API
   
   Article:
   
   Creating a Comprehensive Data Export Workflow from Monday.com Using n8n
   
   If you're managing structured projects in Monday.com, the platform's visual boards and integrations make data management much easier. However, pulling complex datasets—such as all column values, subitems, and linked board relationships from a given item—can be cumbersome without a robust, centralized workflow.
   
   That’s where n8n (short for "nodemation") comes into play. With its low-code automation capabilities and built-in Monday.com connector, n8n can be used to create a powerful data aggregation pipeline that fetches a rich, nested JSON representation of a single Monday item—complete with subitems and board relations.
   
   In this article, we’ll walk through the logic behind a production-ready n8n workflow called “MONDAY GET FULL ITEM,” which accomplishes just that.
   
   Overview: What the Workflow Does
   
   This n8n workflow is triggered with a specific Monday.com item ID (referred to as “pulse”), and performs several chained operations:
   
   - Pulls the item’s basic data (name, ID, column values)
   - Extracts and indexes all column values by both name and ID
   - Scans for board relation-type columns and fetches all linked items
   - Retrieves subitems within a designated “Subitems” column
   - Traverses all subitems and linked items to fetch their full column data
   - Aggregates results into a final JSON object containing the original item, subitems, and board relations
   
   This dataset can then be used for advanced reporting, migration, syncing with other tools, or feeding into downstream analytics.
   
   Core Workflow Components
   
   Let’s break this down into logical sections involved in the workflow:
   
   1. Triggering the Workflow
   
   The workflow starts with an Execute Workflow Trigger node connected to a Set node that defines a variable named pulse (the Monday item ID you wish to query). This allows the workflow to be reusable across different item inputs.
   
   2. Pulling Data from Monday.com
   
   Using the built-in Monday.com Node, the workflow fetches the main item’s data based on the supplied pulse ID. Upon receiving the results, two parallel transformations occur:
   
   - "GET ALL COLUMNS" indexes column values using column IDs
   - "GET ALL COLUMNS2" indexes column values using column names
   
   This helps in future filtering and transformation steps based on user preference or use case.
   
   3. Identifying Board Relations
   
   The “GET ALL RELATIONS” code node filters out columns of type "board_relation," which contain linked item IDs from other boards, also referred to as “linked pulses.”
   
   These linked pulses are processed to extract their IDs in "GET LINKEDPULSES1" and split out using "SPLIT LINKED PULSES1."
   
   Each linked item is fetched using another Monday.com node ("PULL LINKEDPULSE1"), and their full column values are indexed (“GET ALL COLUMNS3”).
   
   4. Pulling Subitems
   
   The “PULL SUBITEMS” node isolates the content of the "Subitems" column and parses its JSON structure to obtain subitem IDs. These are split in “SPLIT SUBITEMS1,” and fetched individually in “GET EACH SUBITEM1” via Monday.com nodes.
   
   Once retrieved, additional transformations occur in “GET ALL COLUMNS1” to parse and flatten the column structure.
   
   5. Compiling and Merging All Data
   
   Three main aggregates are created:
   
   - The main item object with its column data
   - A complete list of all linked board relation items
   - A complete list of all subitems
   
   The workflow uses a series of Merge and Aggregate nodes to combine these datasets into a unified JSON output. This final output contains three major components:
   
   - item: metadata and columns of the original item
   - boardrelations: enriched data of all related board items via board_relation columns
   - subitems: detailed data for each subitem
   
   How to Use the Workflow
   
   This workflow is modular and reusable:
   
   - Drop the workflow into your existing n8n instance.
   - In a separate workflow, use the “Execute Workflow” node and reference this workflow’s ID.
   - Set the desired pulse (item ID) in the input payload to specify the target Monday item.
   
   You'll be able to initiate this workflow dynamically to pull item information as needed.
   
   Tips For Customization
   
   - The name of the subitem column used (“Subitems”) is hardcoded in "PULL SUBITEMS." If your board uses a custom name, update it accordingly.
   - Add additional logic to filter out unnecessary columns or reshape the final payload based on your needs.
   - You can emit the final JSON as a webhook response or push it into another service (e.g., Google Sheets, BigQuery).
   
   Conclusion
   
   This n8n workflow transforms the complex structure of Monday.com items—including their subitems and board relations—into a clear and comprehensive JSON document. It's perfect for users looking to extract and centralize all relevant data for reporting, integrations, backup, or automation purposes.
   
   By abstracting the process into a standalone, reusable component, this solution showcases how visual automation tools like n8n can add powerful data orchestration capabilities to platforms like Monday.com—for both technical and non-technical users alike.

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.