This article provides a complete, practical walkthrough of the Http Schedule Create Scheduled 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:
   Automating GitLab Merge Requests with n8n: A Step-by-Step Workflow Guide
   
   Meta Description:
   Discover how to automate the creation, management, and merging of GitLab merge requests using n8n. This workflow streamlines DevOps processes by integrating with GitLab's API for intelligent CI/CD pipeline automation.
   
   Keywords:
   n8n, GitLab Merge Request Automation, DevOps, CI/CD Automation, n8n Workflow, GitLab API, Open Source Automation, Merge When Pipeline Succeeds, Auto Close Merge Request, GitLab Token, Automation for Developers
   
   Third-Party APIs Used:
   - GitLab REST API (https://gitlab.com)
   
   Article:
   
   Automating GitLab Merge Requests with n8n: A Step-by-Step Workflow Guide
   
   In the ever-evolving DevOps world, automating repetitive tasks like managing merge requests (MRs) in GitLab can significantly improve your development pipeline’s efficiency and consistency. In this article, we’ll explore a powerful n8n workflow that serves as an automation engine to manage merge requests intelligently — from checking for existing MRs, adding notes, and closing obsolete ones, to merging only after the CI/CD pipeline succeeds.
   
   This comprehensive workflow leverages GitLab's REST API in combination with n8n, an open-source automation platform. Let’s dive in.
   
   📌 Overview of the Workflow
   
   The workflow automates the following operations within a GitLab project:
   
   1. Scheduled trigger initiates the workflow.
   2. Check for existing open merge requests from a specific source branch.
   3. If none exist, a new merge request is created.
   4. Add custom notes to the newly created merge request.
   5. Wait 30 seconds for manual approvals or pipeline initiation.
   6. Merge the request automatically if the pipeline passes.
   7. Close stale or duplicate open merge requests from the same source branch.
   
   Let’s break down the components and their roles:
   
   1. Schedule Trigger
   
   The workflow starts with a schedule trigger (e.g. every 30 minutes or daily). The “Schedule Trigger” node initiates the automation on a timeline you define.
   
   2. Check for Existing Merge Requests
   
   Using GitLab’s API, the "API to Check existing merge request" node searches for merge requests that are already open from a specified source branch:
   - Endpoint: /merge_requests
   - Parameters: state=open, source_branch=<sourceBranchName>
   - Authentication: GitLab token
   
   3. Conditional Logic: “Is Exists”
   
   This decision node evaluates whether any open MRs are returned from the API. If the result is empty, the process continues to create a new merge request. Otherwise, it proceeds to manage existing ones.
   
   4. Creating a New Merge Request
   
   If no open MR exists, the "Create New Merge Request" node makes a POST request to GitLab to initiate a new merge:
   - Required fields: source_branch, target_branch, title
   - Endpoint: /merge_requests
   
   5. Add Custom Notes
   
   Immediately after MR creation, the “Add Custom Notes To Merge Request” node appends additional commentary or metadata to the MR through GitLab’s notes API:
   - Endpoint: /merge_requests/<merge_iid>/notes
   - Method: POST
   
   This can help maintain traceability and transparency in your development process.
   
   6. Waiting for Pipeline Results
   
   With a "30 secs wait" node, the workflow temporarily pauses, giving time for required approvals or build pipelines to initialize. This delay helps avoid premature merges.
   
   7. Merge When Pipeline Succeeds
   
   After waiting, a "setValueForMerge" node configures conditions like:
   - Should remove source branch after merge.
   - Whether merge should occur only after pipeline succeeds.
   
   Then, the "Merge When Pipeline Succeeds" node sends a PUT request to GitLab to automate the merge:
   - Endpoint: /merge_requests/<merge_iid>/merge
   - Parameters: merge_when_pipeline_succeeds, should_remove_source_branch
   
   8. Manage Existing or Duplicate MRs
   
   If an MR already exists, the “Loop Over Items” node iterates through them, and the “API to CLOSE existing Merge Request” node updates their state to “closed” if they are no longer needed:
   - Endpoint: /merge_requests/<merge_iid>
   - Method: PUT
   - Payload: state_event=close
   
   📈 Benefits of This Automation
   
   - ⏱ Time Efficiency: Eliminates manual creation, tracking, and merging of MRs.
   - 🧠 Smart Decisioning: Avoids duplicate merge requests and closes outdated ones automatically.
   - 🔐 Secure API Access: Uses GitLab’s token-based authentication for all API operations.
   - 🔄 Keeps Pipelines Clean: Merges only after a successful pipeline run, encouraging healthier code merges.
   
   🔧 Customization Potential
   
   This n8n workflow is fully customizable. You can:
   - Modify the schedule frequency.
   - Add conditions before merging (e.g. review approval count).
   - Integrate Slack or email alerts for newly created or merged requests.
   - Add advanced GitLab labels or assignees automatically.
   
   🔐 GitLab API Reliance
   
   All API requests used in this workflow interact with GitLab’s REST API (https://gitlab.com), making it essential to generate and securely store a PRIVATE-TOKEN credential in your n8n credentials store. This token should have appropriate scope (e.g., ‘api’ or ‘write_repository’) to perform the necessary actions.
   
   ⚙️ Final Thoughts
   
   With this n8n-powered workflow, DevOps teams can ensure predictable, traceable, and efficient merge management directly inside their GitLab environments. Whether you're trying to enforce nicer developer hygiene or simply want things to "just run smoothly," this automation dramatically reduces overhead and improves your CI/CD game.
   
   By combining the flexibility of n8n with the robustness of GitLab, you're setting your development lifecycle up for success.
   
   Ready to supercharge your GitLab merge request workflows? Get started with this n8n automation today!
   
   🔗 Learn more about:
   - n8n: https://n8n.io
   - GitLab API: https://docs.gitlab.com/ee/api/merge_requests.html
   
   —
   
   Written by: Your AI DevOps Assistant 🤖

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.