Retrieve Complete Item Data from Monday.com with Relations and Subitems

MONDAY GET FULL ITEM Workflow Analysis

This N8n workflow template, titled "MONDAY GET FULL ITEM", is designed to extract comprehensive data from a specific item (also known as a "pulse") in Monday.com, including its column values, related items via board relations, and subitems. The goal is to aggregate all nested and relational data into a single, structured JSON output for downstream use such as reporting, integration with other systems, or data synchronization.

The workflow supports deep traversal of Monday.com's hierarchical structure by recursively pulling not just the base item but also any linked pulses (via board-relation columns) and subitems, then normalizing their data into an easily consumable format.

📌 What the Workflow Does

This workflow retrieves a complete snapshot of a Monday.com item, including:

• Basic item metadata (name, ID)
• All column values indexed by both column ID and column name
• Any board-related items (linked via "Board Relation" columns), with full details of those linked items
• Any subitems (child items), with their full column data
• Final aggregation of all this information into one consolidated JSON object

It enables users to get a 360-degree view of a given Monday.com item and all its associated dependencies and relationships in a single API call equivalent.

✅ Key Features and Capabilities

🔧 Main Nodes and Their Purposes

Below is a breakdown of key nodes and their roles in the workflow:

1. Execute Workflow Trigger

• Acts as the starting point.
• Waits for external triggers or manual execution.
• Feeds into the next step that sets up the target item ID.

2. Edit Fields (Set Node)

• Sets a static value: pulse = "4030768878" (example item ID).
• This can be customized per usage to pull different items.
• Allows easy reuse across workflows by changing just this field.

3. Execute Workflow

• Runs the same workflow (workflowId: ZdGZh4qmOqTQe1oq) synchronously.
• Enables encapsulation — you can trigger this logic from another workflow.

4. GET ITEM (Monday.com Get Operation)

• Fetches the main Monday.com item using the provided pulse ID.
• Outputs raw item data including name, ID, column values, and relations.

5. GET ALL COLUMNS / GET ALL COLUMNS2 / GET ALL COLUMNS3 (Code Nodes)

• Transform flat column_values array into a dictionary/object:
  • GET ALL COLUMNS: Maps columns by ID → useful for internal reference.
  • GET ALL COLUMNS2: Maps columns by title/name → better for human readability.
  • GET ALL COLUMNS3: Processes each linked pulse (from relations) similarly.
• Uses helper function createColumnValuesArray() to convert arrays into keyed objects.

6. PULL SUBITEMS (Code Node)

• Parses the value of the "Subitems" column (assumed to exist).
• Extracts the list of subitem IDs from JSON string inside the column value.
• Returns parsed array for further processing.

7. SPLIT SUBITEMS1 & SPLIT LINKED PULSES1 (Split Out Nodes)

• Takes an array of IDs and splits them into individual items.
• Enables one-by-one processing of each subitem or linked pulse.

8. GET EACH SUBITEM1 & PULL LINKEDPULSE1 (Monday.com Get Nodes)

• Retrieve detailed data for each subitem and linked pulse respectively.
• Use dynamic expressions like {{ $json.linkedPulseIds.linkedPulseId }} to pass IDs.

9. GET ALL COLUMNS1 (Code Node)

• Normalizes the column data of each subitem into a clean object format.
• Prepares it for aggregation.

10. GET ALL RELATIONS (Code Node)

• Filters column values to find those of type "board_relation".
• Outputs only relation-type fields so they can be processed.

11. GET LINKEDPULSES1 (Code Node)

• Extracts actual linked pulse IDs from the relation column’s JSON value.
• Returns structured { linkedPulseId }, id, and name.

12. Aggregate & Aggregate1 Nodes

• Collect multiple outputs (e.g., multiple subitems or linked pulses) into arrays.
• Stores results under designated keys:
  • boardrelations: Array of fully resolved related items.
  • subitems: Array of fully resolved subitems.

13. Merge, Merge2, Merge4, Merge1 Nodes

• Combine different data streams:
  • Main item data
  • Column values (by ID and name)
  • Board relations
  • Subitems
• Use mergeByPosition mode to align corresponding items during combination.

14. Sticky Notes

• Provide documentation within the canvas:
  • Explain sections (PULL ALL BOARDRELATION COLUMNS, etc.)
  • Offer instructions on how to use the workflow elsewhere.

💼 Use Cases and Benefits

✅ Ideal For:

• Data Export & Reporting: Generate full snapshots of complex projects/tasks for audit or analysis.
• Integration Syncing: Feed rich item data into CRM, ERP, databases, or custom apps.
• Migration Tools: Extract structured data when moving between boards or platforms.
• Custom Dashboards: Build external dashboards powered by complete Monday.com item context.
• Automation Triggers: Use enriched data to make intelligent decisions in larger automations.

✅ Benefits:

• Comprehensive: No need to manually fetch related data — everything is pulled automatically.
• Structured Output: Data is cleaned, normalized, and organized for immediate use.
• Reusable Design: Can be imported and adapted quickly by updating one parameter.
• Extensible: Easy to add more relation types or handle new column types.
• Visual Clarity: Sticky notes guide users through logic flow even without code knowledge.

🔄 Step-by-Step Workflow Logic

Here is the sequential execution flow:

1. Start Triggered

   • Execute Workflow Trigger begins the process.

2. Set Target Item ID

   • Edit Fields sets pulse = "4030768878" (configurable).

3. Run Self As Sub-Workflow

   • Execute Workflow calls the same workflow ID, passing the pulse value.

4. Fetch Main Item

   • GET ITEM uses the pulse ID to retrieve the base item from Monday.com.

5. Process Main Item Columns

   • Two parallel paths:
     • GET ALL COLUMNS → structures columns by ID
     • GET ALL COLUMNS2 → structures columns by title

6. Extract Subitems

   • PULL SUBITEMS parses the "Subitems" column to get child item IDs.
   • SPLIT SUBITEMS1 breaks the list into individual items.
   • GET EACH SUBITEM1 fetches each subitem’s full data.
   • GET ALL COLUMNS1 transforms each subitem’s columns.
   • Aggregate1 collects all subitems into an array under subitems.

7. Handle Board Relations

   • GET ALL RELATIONS filters out only relation-type columns.
   • GET LINKEDPULSES1 extracts linked pulse IDs from relation data.
   • SPLIT LINKED PULSES1 splits them into separate items.
   • PULL LINKEDPULSE1 fetches each linked item.
   • GET ALL COLUMNS3 formats their column data.
   • Aggregate gathers them into boardrelations.

8. Merge Data Streams

   • Merge4 combines:
     • Relation-filtered data
     • Linked pulse details
   • Result goes to Aggregate → becomes boardrelations
   • Merge2 combines:
     • Main item + column values by ID
     • Column values by name
   • Intermediate merged result

9. Final Aggregation

   • Merge combines:
     • Aggregated boardrelations
     • Aggregated subitems
   • Merge1 merges final piece with main item data.

10. Output Complete JSON

    • Final output contains:

      {
        "item": { "id": "...", "name": "..." },
        "columnValuesById": { ... },
        "columnValuesByName": { ... },
        "boardrelations": [ ... ],
        "subitems": [ ... ]
      }
      

🛠️ How to Use This Template

As noted in Sticky Note3, here’s how to integrate this workflow:

1. Copy these nodes into your desired workflow.
2. Update the workflowId in the Execute Workflow node to match your instance.
3. Modify the pulse value in the Edit Fields node to target the correct Monday.com item.
4. Connect the output to any downstream action (e.g., webhook, database, email).

⚠️ Ensure valid credentials for Monday.com are configured (mondayComApi) before running.

🏁 Conclusion

The "MONDAY GET FULL ITEM" workflow is a powerful, reusable automation tool that unlocks deep visibility into Monday.com items. By combining API calls, JavaScript transformations, data splitting, and aggregation, it delivers a complete, structured dataset ideal for integrations, reporting, and advanced automations.

Its modular design, clear annotations, and self-documenting layout make it accessible to both technical and non-technical users, while remaining flexible enough for enterprise-grade applications.