How to automate video clipping using n8n?

You know that moment in a video, the perfect quote, the highlight, the “wait, run that back” moment? That’s the part everyone wants to share.

But getting from full-length video to clean, clipped highlight is... not fast. Manually trimming videos takes time. Doing it over and over again? That’s time you're not spending building things that matter.

So we automated it.

With n8n and FastPix, you can go from long-form video to precisely clipped, ready-to-publish shortform content automatically. No video editor. No exporting. No timeline scrubbing. Just a simple workflow that clips the moment you want, when you want it, every single time.

Let’s set it up.

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Why automating video clipping?

Because doing it manually doesn’t scale. Not when you’re working with live streams, user-generated uploads, or just more content than one person can reasonably drag across a timeline.

Traditional editing tools are fine, until you need to clip ten videos a day, across multiple platforms, with frame-level precision. That’s where automation pays off:

• Save time by turning repeatable steps into reusable workflows

• Scale up without hiring more editors or writing glue code

• Get precise using timestamps, metadata, or AI to target the moments you care about

• Lower cost by reducing hands-on effort and speeding up delivery

With n8n as your automation engine and FastPix handling the actual clipping via API, you get a clean, scalable pipeline, from ingestion to distribution with almost zero manual work.

Let’s build it.

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What you’ll need before we get started

This workflow won’t take much to set up, but here’s what you’ll want on hand:

1. An n8n instance: Self-hosted or cloud, either works. You can run it locally with Docker or sign up at n8n.io to use their hosted version.

2. A FastPix account: Head over to dashboard.fastpix.io and grab your API access credentials (Token ID + Token Secret). You’ll need these to authenticate clipping requests.

3. A video file to clip: We’ll assume it’s a public URL (like one from Google Drive), but you can pull from any source as long as it’s accessible via HTTP.

4. A little n8n knowledge (optional): You don’t need to be a workflow wizard. We’ll walk through everything step-by-step. But if you’ve used n8n before, you’ll feel right at home.

5. (Optional) A destination to upload your clips: YouTube Shorts? TikTok? Google Drive? You can plug this in at the end of the flow if you want automated publishing too.

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Step 1: Understanding how n8n and FastPix work together

n8n, for automation and control

n8n is an open-source automation platform that lets you connect APIs, services, and logic into structured workflows. It’s node-based, which means you can build out logic visually,  schedule triggers, HTTP requests, loops, and conditions, without needing to spin up a backend.

For video tasks, this makes it ideal. You can fetch video sources, pass timestamps, make API calls to processing services, and route outputs wherever you want, all from one interface.

FastPix for precise, API-first video clipping

FastPix provides APIs for on-demand video processing,  including clipping, encoding, and delivery. In this workflow, it’s used to extract exact segments from a video based on start and end times.

The clipping endpoint supports:

• Timestamp-based extraction with frame accuracy

• Output in multiple resolutions and formats

• Instant playback support via generated URLs

• Secure access via token-based authentication

You send a video URL and timestamps, FastPix returns a processed clip, no manual trimming, no export steps, no video editor needed.

When you connect n8n’s automation flow with FastPix’s API, you get a reliable, repeatable way to generate and publish clips with minimal overhead.

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Step 2: Build the n8n workflow

Let’s walk through setting up your automated video clipping flow in n8n. The workflow will do the following:

1. Trigger on a schedule or manual run

2. Fetch a video file from a public URL or connected service

3. Call the FastPix API to create a clip

4. Poll for processing status

5. Download the final clip

6. (Optional) Upload it somewhere like YouTube

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1. Create a new workflow

• Open your n8n instance (local or hosted)

• Click “New Workflow”

• Give it a name like “Video Clipping with FastPix”

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2. Add a trigger node

You can start the workflow either manually (for testing) or on a schedule (for automation):

• For testing, add a Manual Trigger node

• For automated runs, use a Schedule node (e.g., 0 0 * * * for midnight)

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3. Fetch the video source

If your video is stored on Google Drive:

• Add a Google Drive node

• Authenticate using OAuth2

• Set the operation to “Download a file”

• Provide the file ID or public URL

• Save it to a temp location (for self-hosted, something like /data/shared)

If your video is already hosted publicly (e.g., on S3 or CDN), you can skip this and use a static URL directly.

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4. Send the FastPix clipping request

Add an HTTP Request node to call the FastPix API:

Method: POST

URL: https://api.fastpix.io/v1/on-demand

Headers:

Content-Type: application/json

Authorization: Basic <base64 encoded Token ID:Token Secret

Body (JSON):

1{ 
2  "inputs": [ 
3    { 
4      "type": "video", 
5      "url": "https://static.fastpix.io/sample.mp4", 
6      "startTime": 2, 
7      "endTime": 30 
8    } 
9  ] 
10} 

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This sends a request to create a clip between 2s and 30s from the provided video URL. FastPix returns a clip ID you’ll use to track status.

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5. Wait and check processing status

Video processing isn’t always instant, so:

• Add a Wait node (e.g., 10 seconds)

• Then add another HTTP Request node to poll the clip status

Correct the polling method, use GET, not POST:

• Method: GET
• URL: https://api.fastpix.io/v1/on-demand/{{ $json.id }}
• Use the clip ID returned earlier
• If status is still processing, loop back to the wait node and try again
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6. Download the completed clip

Once the status is completed, FastPix will return a playable asset. You can build the download URL using the playback ID:

bash

https://stream.fastpix.io/{{ $json.data.playbackIds[0].id }}/capped-4k.mp4

• Add a new HTTP Request node

• Method: GET

• URL: the above FastPix stream URL

• Download the video and save it to a temp path or pass the binary data to the next node

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7. (Optional) Upload the clip to another platform

If you want to push the final clip somewhere like YouTube:

• Add a YouTube node

• Authenticate with your Google account

• Set operation to Upload Video

• Map the file from the previous step

• Add a title and description, e.g., “Clip from latest livestream”

8. Test the workflow

• Click Save

• Use Test Workflow to run it manually

• Check node outputs and FastPix API responses for errors

• Once it works, enable the workflow and let it run on schedule

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Step 3: Make it smarter (and more scalable)

The basic workflow works, but if you’re handling real-world volume or different input sources, a few upgrades can make it more dynamic and resilient.

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Use dynamic clipping parameters

Hardcoding timestamps is fine for testing. But in production, you’ll want to pull startTime and endTime from somewhere else, like a Google Sheet, a webhook payload, or a database.
Add a Google Sheets node or Webhook Trigger to fetch timestamp values dynamically. This makes your workflow reusable for different videos.

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Add error handling

APIs sometimes fail. Network issues, bad input, expired tokens, it happens. Add an If node after the FastPix request or status check. If the response status isn’t 200 or the job fails, send a notification using Slack, Email, or any other n8n integration. This helps you catch failures without manually checking logs.

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Publish to multiple platforms

You don’t have to stop at YouTube. Extend the flow to support TikTok, Instagram Reels, or anywhere else your audience lives. You can either:

• Use official API nodes (where available), or

• Integrate with services like upload-post.com to simplify multi-platform publishing

Automate timestamp detection with AI

Don’t want to manually mark highlights? Use AI to find them for you. Add a transcription step with OpenAI Whisper or a similar speech-to-text service. Then scan the text for keywords, speaker moments, or chapters, and pass those timestamps into FastPix for automated clip generation.

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Step 4: Use the sample workflow to speed things up

Don’t want to start from scratch? No problem. Here’s a minimal n8n workflow that handles the core logic: trigger → FastPix clip request → download result.

You can import this JSON directly into your n8n editor and modify as needed.

A quick note before you import:

• Replace the authorization header with your actual FastPix Token ID and Token Secret.

• Update the video URL and timestamps to suit your use case.

• This example doesn’t include error handling or polling, you’ll want to add those for production.

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1{ 
2  "nodes": [ 
3    { 
4      "parameters": {}, 
5      "type": "n8n-nodes-base.manualTrigger", 
6      "typeVersion": 1, 
7      "position": [0, 0], 
8      "id": "a5fb32a0-5a71-4859-a8c0-30c819116608", 
9      "name": "Manual Trigger" 
10    }, 
11    { 
12      "parameters": { 
13        "method": "POST", 
14        "url": "https://api.fastpix.io/v1/on-demand", 
15        "sendHeaders": true, 
16        "headerParameters": { 
17          "parameters": [ 
18            { 
19              "name": "accept", 
20              "value": "application/json" 
21            }, 
22            { 
23              "name": "authorization", 
24              "value": "Basic <REPLACE_WITH_YOUR_BASE64_TOKEN>" 
25            } 
26          ] 
27        }, 
28        "sendBody": true, 
29        "specifyBody": "json", 
30        "jsonBody": "{\n  \"accessPolicy\": \"public\",\n  \"optimizeAudio\": false,\n  \"maxResolution\": \"1080p\",\n  \"inputs\": [\n    {\n      \"url\": \"https://static.fastpix.io/sample.mp4\",\n      \"startTime\": 0,\n      \"endTime\": 60,\n      \"type\": \"video\"\n    }\n  ],\n  \"mp4Support\": \"capped_4k\"\n}", 
31        "options": {} 
32      }, 
33      "type": "n8n-nodes-base.httpRequest", 
34      "typeVersion": 4.2, 
35      "position": [220, 0], 
36      "id": "17b422f7-e0c3-48d5-a4c1-919997b44724", 
37      "name": "Send to FastPix" 
38    }, 
39    { 
40      "parameters": { 
41        "url": "=https://stream.fastpix.io/{{$json.data.playbackIds[0].id}}/capped-4k.mp4", 
42        "options": {} 
43      }, 
44      "type": "n8n-nodes-base.httpRequest", 
45      "typeVersion": 4.2, 
46      "position": [440, 0], 
47      "id": "a817fa2a-22b7-46b0-908f-4a8e6a770649", 
48      "name": "Download Clip", 
49      "retryOnFail": true, 
50      "maxTries": 5 
51    } 
52  ], 
53  "connections": { 
54    "Manual Trigger": { 
55      "main": [ 
56        [{ "node": "Send to FastPix", "type": "main", "index": 0 }] 
57      ] 
58    }, 
59    "Send to FastPix": { 
60      "main": [ 
61        [{ "node": "Download Clip", "type": "main", "index": 0 }] 
62      ] 
63    } 
64  } 
65}

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Once imported, run the workflow manually and check the outputs. If all goes well, you’ll get a downloadable clip URL from FastPix.

Let me know if you want a full version that includes polling, retry logic, or dynamic inputs, happy to expand this next.

Step 5: A few best practices before you scale this up

Once your workflow is running, here are a few things worth keeping in mind:

• Track your usage: FastPix runs on a pay-as-you-go model, so keep an eye on your API usage in the dashboard, especially if you’re processing clips in bulk.

• Run n8n locally if needed: If you're dealing with sensitive videos or private URLs, self-hosting n8n via Docker is a good move. You get full control over where your data lives.

• Test as you build: Don’t wait until the end to debug. Test each node as you add, it’s much easier to catch issues early than hunt for them in a finished flow.

• Back up your clips: Once a clip is created, push it somewhere reliable, Google Drive, S3, wherever you store assets. It’s always smart to keep a copy outside the workflow.

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Video clipping with FastPix and n8n

Combining n8n’s workflow automation with FastPix’s video APIs gives you a powerful way to automate clipping, repurposing, and publishing video content at scale.

From one API, you get:

• Precise timestamp-based clipping

• Video tagging and chapter detection

• Speech-to-text transcription and multilingual translation

• AI-generated highlights from live or on-demand videos

• And full support for upload, transform, and stream workflows

Whether you’re building social media highlights, auto-recaps from live streams, or a fully automated content pipeline, FastPix with n8n lets you move faster, with less manual work.

FastPix is also available as SDKs in Node.js, Python, Go, PHP, and C#, so you can integrate in whatever stack you already use. Sign up to try FastPix and get $25 in free credit.