This article provides a complete, practical walkthrough of the Wait Manual Automate 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:  
   Fully Automated Video Captioning with json2video and n8n
   
   Meta Description:  
   Learn how to automate the process of generating captions for your videos using json2video and n8n. This no-code workflow makes it easy to add professional subtitles with zero manual editing.
   
   Keywords:  
   video captions automation, json2video, n8n workflow, subtitling automation, no-code video editing, generate subtitles automatically, subtitle API, video processing automation, json2video API, n8n tutorial
   
   Third-Party APIs Used:
   
   1. json2video API: https://api.json2video.com – Used to create and monitor video projects with embedded subtitles.
   2. Amazon S3 – Source of the hosted video file. While not directly part of the API interaction, the video file is served via a public S3 URL.
   3. n8n: An automation tool (open source) used here to orchestrate the captioning workflow.
   
   —
   
   Article:
   
   Automating Video Captions with json2video and n8n: A No-Code Workflow for Professionals
   
   Adding captions to your videos can significantly increase audience engagement, accessibility, and overall production quality. However, manually captioning videos is time-consuming and often prone to formatting inconsistency. That’s where automation tools like n8n and json2video come into play.
   
   In this article, we’ll walk you through a fully automated workflow that generates professional captions and embeds them into your videos using a no-code setup powered by n8n and the json2video API.
   
   Let’s explore how this workflow works and how you can implement it for your own video projects in just a few steps.
   
   What is json2video?
   
   json2video is a powerful cloud-based video rendering service that enables users to create or modify videos programmatically using JSON. It supports complex video editing functions, including subtitles, scenes, transitions, and visual styles – all composable via code or API requests.
   
   What is n8n?
   
   n8n is an open-source workflow automation tool that allows you to connect APIs, services, and your own applications without writing complex code. In this use case, it acts as the glue between static video files and the json2video API to build an automatic captioning pipeline.
   
   Workflow Overview: End-to-End Captioning
   
   This specific n8n workflow does the following:
   
   1. Takes a video URL and custom dimensions (width and height).
   2. Sends the video to json2video with subtitle specifications.
   3. Periodically checks the rendering status.
   4. Handles errors gracefully or continues polling until rendering is complete.
   5. Outputs the final video URL and metadata: duration, resolution, size, and remaining API quota.
   
   Let’s break down the key components.
   
   Step 1: Trigger the Workflow
   
   The workflow begins with a manual trigger node labeled "When clicking ‘Test workflow’." This allows users to test and iterate on the configuration in real time.
   
   Step 2: Define Video Input
   
   Next, a Set node titled “Config” assigns three important values:
   - video_url: The URL to the video that needs captions.
   - width & height: The dimensions for output formatting (e.g., 1080x1920 for vertical video).
   
   These values are easily modifiable to accommodate different video files or screen formats.
   
   Step 3: Send Captions Request to json2video
   
   A crucial part of the workflow is the HTTP Request node "json2video - Add Captions." This node sends a POST request to json2video’s movie creation endpoint with the following details:
   - Video source.
   - Subtitle element, language code `'en'`.
   - Styling preferences including font, size, colors, and shadows.
   
   Example styling includes:
   - Font: Oswald
   - Size: 140
   - Box color: Rich dark (#260B1B)
   - Word and line colors for contrast
   
   This configurability enables you to match your branding or video aesthetic consistently.
   
   Step 4: Poll for Video Rendering Status
   
   After sending the request, the workflow waits for a short period (10 seconds) using a Wait node. It then checks video rendering status by sending another request via "json2video - Get Status."
   
   Then the workflow uses two conditional logic (If) nodes:
   - Is Error: Checks whether the video encountered a rendering error.
   - Is Completed: Determines whether rendering status is marked as “done.”
   
   Error paths lead to a NoOp node allowing for graceful handling, while completed videos move to the final output stage.
   
   Step 5: Output Final Result
   
   Once the rendering is complete, a final Set node outputs key metadata:
   - URL to rendered video
   - Duration, size, width, and height
   - Rendering time
   - Remaining quota from json2video, helpful for rate limiting usage
   
   End Result: Your video is now captioned, styled, and hosted—all automated!
   
   Why Automate with json2video and n8n?
   
   - ⏱ Time Savings: Reduce hours of manual subtitle syncing to just seconds.
   - 🎨 Consistent Design: Style captions once and re-use them across projects.
   - 🧠 Smart Polling: Automatically waits and checks for rendering without manual refresh.
   - 🔧 Modifiable: Change layouts, subtitle languages, or inputs on demand.
   - 🧩 Extensible: Easily connect this pipeline to Google Drive, Dropbox, Airtable, or social publishing tools.
   
   Getting Started
   
   📌 To use this workflow, you need:
   
   1. A json2video account and API key.
   2. Defined HTTP credentials in n8n using Custom Auth with the `x-api-key`.
   3. A video file accessible via URL (S3, CDN, Cloudinary, etc.).
   4. n8n either self-hosted or cloud instance.
   
   For step-by-step details, json2video provides onboarding guides and n8n has strong community documentation to help you integrate new services.
   
   Conclusion
   
   Creating captioned videos at scale doesn’t have to be hard or time-consuming. Thanks to the power of json2video and n8n, you can now build a professional, automated captioning pipeline in minutes.
   
   Whether you're a content creator, social media manager, or run a production team — this automation can save you time, reduce errors, and produce high-quality videos optimized for any platform.
   
   —
   
   Try json2video for yourself:  
   👉 https://json2video.com/?afco=manu 👈
   
   Explore more workflows and tutorials at:  
   https://n8n.io/workflows
   
   —
   
   Need help customizing this pipeline? Reach out to the community forums or AI automation consultants for personalized guidance.

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.