This article provides a complete, practical walkthrough of the Stickynote Gmail Create 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:
   Smart Gmail Automation with n8n: Auto-Categorize Emails Using AI and Gmail Labels
   
   Meta Description:
   Discover how to automate email organization in Gmail using n8n and AI. This smart workflow labels emails based on content, creates new labels when needed, and keeps your inbox clean and categorized.
   
   Keywords:
   n8n workflow, Gmail automation, email labeling, OpenAI, Gmail API, label emails automatically, categorize Gmail, AI email assistant, n8n tutorials, Gmail label management, workflow automation, Langchain agent
   
   Third-Party APIs Used:
   
   1. Gmail API
      - Used for triggering on new emails, reading labels, creating labels, retrieving messages, and assigning labels.
   
   2. OpenAI API
      - Provides the GPT-powered AI logic to analyze email content and determine appropriate labels based on custom instructions.
   
   —
   
   Article:
   
   Automate Gmail Labeling with n8n and AI: A Smart Email Categorization Workflow
   
   Managing the constant stream of emails in your inbox can quickly become overwhelming—especially when messages are poorly organized. Fortunately, with low-code automation platform n8n, you can now build intelligent workflows to declutter your inbox using AI. In this article, we’ll explore a powerful Gmail labeling workflow that uses OpenAI's language model to analyze email content and automatically assign or create Gmail labels accordingly.
   
   📧 The Problem: Inbox Chaos
   
   Many professionals rely heavily on Gmail to manage both work and personal communications. Over time, email folders overflow, and manually assigning labels becomes tedious. Without consistent categorization, finding important messages can turn into a chore. That’s where automation comes in.
   
   ⚙️ The Solution: A Smart Labelling Agent Powered by n8n
   
   This n8n workflow harnesses the Gmail API and OpenAI to create an AI-driven labeling assistant. Here's how it works:
   
   1. A Gmail Trigger polls your inbox every five minutes.
   2. When a new email is received, the workflow:
      - Retrieves the email message.
      - Fetches existing labels in your Gmail account.
      - Analyzes the email’s content (including subject, sender, keywords).
      - Assigns an existing label or creates a new one, keeping your labeling structure intact.
   
   It even removes the “Inbox” label if the email is deemed low-priority (think promotions or ads), helping you maintain a cleaner inbox view.
   
   🔗 How It Works – Pipeline Breakdown
   
   Let’s walk through the key components of the workflow, based on the n8n nodes used:
   
   1. Gmail Trigger Node
      - Polls Gmail every 5 minutes for new emails.
      - Connects via OAuth2 credentials for secure access.
   
   2. Wait Node
      - Introduces a brief pause to manage processing loads or rate limits.
   
   3. AI-Powered Email Labelling Agent (LangChain Agent Node)
      - This is where the magic happens. The agent receives the new email and:
        - Reads existing Gmail labels (via Gmail API).
        - Retrieves the actual email message.
        - Processes the content using OpenAI's chat model.
        - Matches it with the most appropriate existing label or creates a new label if needed.
        - Assigns the matched label and optionally removes the "Inbox" label.
   
   4. OpenAI Chat Model Node
      - Uses the GPT model with a system message outlining detailed logic and a prompt based on the email content.
      - Helps interpret context from the email and guides decisions on labeling.
   
   5. Gmail Tool Nodes
      - Gmail - Read Labels: Retrieves all available labels.
      - Gmail - Get Message: Pulls the full email content using the Gmail message ID.
      - Gmail - Add Label to Message: Applies one or more labels to the specific email.
      - Gmail - Create Label: If no existing label fits, this node creates a new one, formatted to align with your structure.
   
   6. Memory Management
      - A memory buffer using LangChain’s memory management allows the agent to track session context and avoid redundant operations if the workflow loops or iterates.
   
   💡 Smart Labeling Rules Implemented
   
   The workflow isn't just blindly assigning labels. It follows customized GPT instructions to ensure labels are meaningful and structured coherently. A few core principles include:
   
   - Match existing labels where possible.
   - Create new labels only if necessary.
   - Maintain hierarchy using sublabels (e.g., “AI/Updates”).
   - Strip “Inbox” label if the email is categorized as low priority (e.g., ads or promotions).
   
   Sample logic includes:
   - Emails with titles like “Project Alpha Update” go under “[Project Alpha]”.
   - “New Vendor Inquiry” would initiate a label like “Vendor Inquiry” under a parent if one doesn’t exist.
   
   📈 Outcome: A Cleaner, Smarter Gmail Inbox
   
   With this Gmail automation in place, your inbox effectively manages itself. High-value emails stay put, distractions move out of sight, and new topics naturally build new label hierarchies. This allows for:
   
   - Faster email retrieval.
   - Less time spent organizing messages manually.
   - Consistent label structure aligned with your preferences.
   
   🛠️ Getting Started
   
   To deploy this workflow yourself, you’ll need:
   
   - An n8n instance (cloud-hosted or self-hosted).
   - Connected Google account with Gmail API enabled via OAuth2.
   - OpenAI API Key (for GPT functionality).
   - Proper permissions and scopes assigned in your Gmail credentials.
   
   Once set up, this AI-augmented automation becomes a hands-free virtual assistant, quietly organizing your data in real time.
   
   —
   
   In today’s digital world, keeping a clean inbox is vital to maintaining productivity and focus. With the collaborative power of OpenAI and Gmail’s robust API, n8n allows you to automate, adapt, and optimize your email workflows effortlessly.
   
   Start building smarter today—with just a few nodes and the power of AI.
   
   — 
   
   Want more tutorials like this? Subscribe for our latest low-code automation workflows and smart 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.