This article provides a complete, practical walkthrough of the Splitout Filter Create Webhook 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:  
   Using n8n and GPT-4 to Automatically Draft Email Replies in Fastmail
   
   Meta Description:  
   Discover how to automate your email reply process using n8n, OpenAI's GPT-4, and Fastmail's JMAP API. This workflow intelligently drafts responses to new IMAP emails and saves them in your Fastmail Drafts folder.
   
   Keywords:  
   n8n email automation, Fastmail API JMAP, AI email response, OpenAI GPT-4, GPT-4 email bot, draft reply automation, IMAP email trigger, automated email writing, n8n workflow GPT, reply email generator, fastmail GPT integration
   
   Third-Party APIs Used:
   
   1. Fastmail JMAP API – Used to fetch session data, mailbox IDs, and upload generated drafts to the "Drafts" folder.
   2. OpenAI API – Utilized for generating natural-sounding, context-aware email replies using GPT-4.
   3. IMAP (Email Read) – Monitors an inbox for new and unread emails to trigger the workflow.
   
   —
   
   Article:
   
   Automating Your Email Replies with n8n, GPT-4, and Fastmail
   
   Managing email replies can be one of the most time-consuming aspects of digital communication. Whether you're handling client queries, coordinating with colleagues, or just keeping your inbox neat, replying to emails takes both time and mental energy. Fortunately, automation tools like n8n are enabling a whole new level of productivity.
   
   This article explores a powerful n8n workflow that leverages OpenAI's GPT-4 and Fastmail's JMAP API to automatically generate and save email replies—ready for editing or sending. By setting this up, you can handle personal or professional correspondence much more efficiently with AI-assisted responses.
   
   Overview of the Workflow
   
   The n8n workflow consists of several interconnected nodes, each performing a specific task. Here's how it works in sequence:
   
   1. Incoming Email Detection via IMAP  
   The process is initiated when a new, unread email lands in your inbox. n8n constantly monitors your specified IMAP account using the built-in Email Trigger (IMAP) node. This node can be configured with filters, such as only processing emails marked as "UNSEEN."
   
   2. Data Extraction from the Email  
   Once a new email is identified, the workflow moves to extract critical pieces of data: the plain text version of the email body, the sender’s address, the subject line, and metadata such as the "message-id" and "reply-to" information. These details are essential for creating a coherent and contextually appropriate response.
   
   3. AI-Powered Response Drafting via GPT-4  
   With the relevant email content extracted, it's passed to GPT-4 through the OpenAI node. Using a carefully crafted prompt, the AI is instructed to analyze the original email and generate a friendly, casual response. It incorporates appropriate greetings and sign-offs, retaining formality or informality depending on the phrasing found in the original email.
   
   For example, if the email uses "Sie" (formal German), the response will mirror that tone. The AI generates a text-only reply without any headers or formatting—just the message body, perfect for dropping into a reply draft.
   
   4. Session Initialization and Mailbox Discovery via Fastmail API  
   To send the reply to the correct location, the workflow first contacts Fastmail’s JMAP API to retrieve session information. This includes details such as the authenticated user and available mailboxes. Next, it makes another call to fetch all mailbox IDs associated with the account.
   
   5. Finding the Drafts Folder  
   From the list of mailbox IDs, the workflow filters out the one associated with the "drafts" role. This is where the auto-generated response will be saved, allowing the user to review or edit before sending.
   
   6. Assembling the Draft Email  
   After obtaining all required data—recipient's address, sender info, subject, and AI-generated content—the workflow prepares the email in the required format. It references the original email's message ID for continuity, includes proper labeling (like “$draft”), and formats the response content as plain text.
   
   7. Pushing the Draft to Fastmail  
   Finally, using the Fastmail JMAP API again, the workflow uploads the prepared reply to the user's "Drafts" folder. This means the original sender doesn’t receive a response immediately; instead, the email is saved as a draft for human review, providing a safety net and preserving editorial control.
   
   Why This Matters
   
   - Saves Time: You can save hours of daily email workload, especially for routine responses.
   - Reduces Cognitive Load: By letting AI draft the first version, you only need to fine-tune and hit send.
   - Enhances Consistency: Maintain a consistent tone and quality in your communications with AI-generated replies.
   - Privacy Preserved: Since the email is only saved as a draft, no message is sent without review.
   
   Prerequisites to Set This Up
   
   Before implementing this workflow, ensure you have the following:
   
   - A configured IMAP-compatible email account (can be Gmail, Fastmail, etc.) integrated in n8n.
   - A Fastmail account with JMAP API access enabled. Credentials must be correctly set up as HTTP Header Auth in n8n.
   - An API key from OpenAI with access to GPT-4, integrated securely in n8n.
   
   Conclusion
   
   This n8n workflow is a great blend of automation, language intelligence, and user control. It adds real value by automating repetitive tasks without completely removing the human from the loop. Whether you're using Fastmail for personal communication or business purposes, integrating AI and automation in this way brings a modern, efficient, and context-aware edge to your email workflow.
   
   If you're looking to scale your productivity and reduce email fatigue, this workflow is a great place to start.
   
   —  
   Need help implementing this setup in your n8n instance? Let us know, and we’ll guide you through it!

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.