Convert Make.com blueprints to workflows with Azure OpenAI and Google Sheets

Workflow Reference: AI-Powered Make.com to n8n Migration Engine

This document provides a technical breakdown of the n8n workflow designed to automate the conversion of Make.com blueprint JSON files into valid, importable n8n workflow exports using Azure OpenAI.

1. Workflow Overview

The purpose of this workflow is to bridge the gap between Make.com and n8n by programmatically remapping logic, connections, and node configurations. It eliminates manual migration effort by using an AI agent trained on n8n's schema requirements.

Logical Blocks:

1.1 Trigger & Discovery: Manual initiation followed by scanning Google Drive for target blueprint files.
1.2 Data Preparation: Downloading the binary file and extracting the JSON content.
1.3 AI Intelligence: An AI Agent (GPT-4o-mini) processes the Make.com JSON and outputs a structured n8n JSON.
1.4 Post-Processing: Refinement of the AI output to ensure strict schema compliance (fixing connections and conditions).
1.5 Export: Saving the finalized JSON to a Google Sheet for review or programmatic retrieval.

2. Block-by-Block Analysis

2.1 Trigger & File Discovery

Overview: Locates the source file within a cloud storage environment.
Nodes Involved: When clicking ‘Execute workflow’, Search Files and Folders, Filter Target Blueprint.
Node Details:
- Search Files and Folders (Google Drive): Configured to list files. It requires Google Drive OAuth2 credentials.
- Filter Target Blueprint (IF Node): Checks if the filename contains the string "blueprint".
- Edge Cases: If multiple files contain "blueprint", the workflow proceeds with all of them, potentially triggering multiple AI runs.

2.2 Download & Parse

Overview: Converts a cloud file reference into usable JSON data.
Nodes Involved: Download Blueprint File, Extract JSON from File.
Node Details:
- Download Blueprint File (Google Drive): Downloads the file using the id from the previous step. Output is a binary object.
- Extract JSON from File: Converts the binary file content into a standard n8n JSON object so the AI can read it.

2.3 AI Conversion

Overview: The "brain" of the workflow that performs the technical mapping.
Nodes Involved: Convert Blueprint with AI Agent, Azure OpenAI Chat Model.
Node Details:
- Convert Blueprint with AI Agent: Uses a detailed system prompt to enforce n8n schema rules (e.g., forcing main connection types, mapping google-sheets:watchRows to googleSheetsTrigger).
- Azure OpenAI Chat Model: Configured with gpt-4o-mini. Requires a scoped Azure deployment and API key.
- Key Expression: {{ JSON.stringify($json.data) }} sends the raw Make.com data to the LLM.

2.4 Cleanup & Transform

Overview: Programmatic "sanitization" of the AI's output to ensure 100% import compatibility.
Nodes Involved: Normalize Connections and Conditions, Strip Make Fields and Finalize.
Node Details:
- Normalize Connections and Conditions (Code): Maps Node IDs back to Node Names (as n8n requires names for connections) and fixes "IF" node structures that the AI might format incorrectly.
- Strip Make Fields and Finalize (Code): Removes Make-specific metadata (like __IMTCONN__) and strips typeVersion and versionId to prevent version mismatch errors during import.

2.5 Export

Overview: Stores the result in an external database/sheet.
Nodes Involved: Save Converted Workflow to Sheet.
Node Details:
- Google Sheets: Appends the final JSON string into a designated column.
- Requirements: Requires a pre-existing Spreadsheet ID and a sheet named "json".

3. Summary Table

Node Name	Node Type	Functional Role	Input Node(s)	Output Node(s)	Sticky Note
When clicking ‘Execute workflow’	manualTrigger	Workflow Entry	(None)	Search Files and Folders	Starts on manual execution...
Search Files and Folders	googleDrive	File Discovery	Manual Trigger	Filter Target Blueprint	Starts on manual execution...
Filter Target Blueprint	if	File Validation	Search Files	Download Blueprint File	Starts on manual execution...
Download Blueprint File	googleDrive	Data Retrieval	Filter	Extract JSON from File	Downloads the matched blueprint...
Extract JSON from File	extractFromFile	Data Parsing	Download	AI Agent	Downloads the matched blueprint...
Convert Blueprint with AI Agent	agent	AI Translation	Extract JSON	Normalize Connections	The Azure OpenAI-powered agent...
Azure OpenAI Chat Model	lmChatAzureOpenAi	LLM Provider	(None)	AI Agent	(None)
Normalize Connections and Conditions	code	Data Refinement	AI Agent	Strip Make Fields	Two code nodes clean up...
Strip Make Fields and Finalize	code	Data Finalization	Normalize	Save to Sheet	Two code nodes clean up...
Save Converted Workflow to Sheet	googleSheets	Data Storage	Strip Make Fields	(None)	(None)

4. Reproducing the Workflow from Scratch

Preparation:
- Set up Google Drive & Sheets OAuth2 credentials.
- Set up Azure OpenAI credentials and deploy a gpt-4o-mini or gpt-4o model.
File Input Stage:
- Add a Manual Trigger.
- Add a Google Drive Node (Search), set Resource to "File", and Operation to "List".
- Add an IF Node to filter files where the name contains "blueprint".
- Add another Google Drive Node (Download) using the id from the search.
- Add an Extract from File Node, setting the operation to "JSON".
AI Integration:
- Add an AI Agent Node. Connect an Azure OpenAI Chat Model node to its tool/model input.
- Prompt Configuration: Paste a system message instructing the model to output only valid n8n JSON, mapping modules like builtin:BasicRouter to n8n-nodes-base.if.
The Logic Fix (Code Node 1):
- Create a Code Node named "Normalize Connections".
- Write a script to iterate through the connections object, replacing ID keys with Name keys.
- Ensure "IF" node conditions use the string or boolean arrays correctly.
The Cleanup (Code Node 2):
- Create a second Code Node.
- Write a script to delete parameters.__IMTCONN__ from all nodes and remove top-level fields like active and versionId.
Final Export:
- Add a Google Sheets Node (Append).
- Map the json column to the output of the final Code node.

5. General Notes & Resources

Note Content	Context or Link
Ensure the target Google Sheet has a header named "json" in the first row.	Setup Requirement
Use n8n version 1.0+ for compatibility with the AI Agent node.	Version Note
Azure OpenAI deployment name must match the model name used in the credentials.	Credential Setup
For large blueprints, increase the timeout in the AI Agent node settings.	Performance

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