VideoUpscaler AI Video Upscaler (4K/60fps)

AI Video Upscaler

Turn blurry, low-resolution video into sharp 1080p, 2K or 4K , in your browser, from your code, or by asking your AI assistant.

Try it free · API docs · MCP server · Integrations & n8n · Pricing

VideoUpscaler is an online AI video upscaler. Upload a video, pick a resolution, and download a sharper version a few minutes later. There's nothing to install and you don't need a graphics card: the AI runs on our GPUs, not on your computer.

This repository is the public home of the product: how to use it, which AI model it runs, ready-to-copy examples for the REST API and MCP server, and an agent skill.

Contents

• What it does
• What you need
• Three ways to use it
• 1. Website (no code)
• 2. MCP server (ask your AI assistant)
• 3. REST API (for developers)
• 4. Workflow Automation & n8n Integration
• The AI model
• Pricing
• Limits
• FAQ

What it does

• Upscales video to 1080p, 2K or 4K. Old home movies, 480p/720p downloads, phone clips, screen recordings, anime and game footage.
• Restores detail, not just pixels. Plain resizing only stretches a blurry frame. The AI model rebuilds edges, faces, textures and text, and reduces blur, noise and compression blocks.
• Keeps the video stable. Frames are processed as a video, not as separate photos, so details don't flicker from one frame to the next.
• Keeps your audio. The soundtrack is copied to the result unchanged.
• Works everywhere. Any modern browser on Windows, macOS, Linux, iPhone, iPad or Android.

What you need

All the heavy lifting (decoding, AI inference, encoding) happens on our GPUs. A five-year-old laptop gets exactly the same result as a high-end workstation.

Three ways to use it

1. Website (no code)

Best for: anyone who just wants a sharper video.

1. Go to [videoupscaler.co](https://videoupscaler.co) and sign in with Google or your email. New accounts get 10 free credits.
2. Drop your video into the upload box (or click to choose a file).
3. Pick 1080P, 2K or 4K. The page shows how many credits the video needs before you start.

1. Click Start Upscaling. Keep the tab open, or come back later: finished videos stay in your history.
2. Drag the slider to compare before and after, then click Download.

Tips for the best result:

• Upload the original file, not a re-downloaded or screen-recorded copy. Every re-encode throws detail away.
• Try a short clip first (5–10 seconds) to check the look before you upscale a long video.
• 1080p is enough for most 480p/720p sources. Choose 2K or 4K when you'll watch on a large screen or edit in a 4K timeline.

Free results carry a small "videoupscaler.co" watermark. After your first purchase, new results have no watermark.

2. MCP server (ask your AI assistant)

Best for: people who already work in Claude, Cursor or VS Code and want to say *"upscale this video to 4K"* instead of opening a website.

Two ways to connect:

• Remote Streamable HTTP: https://videoupscaler.co/api/mcp (listed in the MCP Registry as co.videoupscaler/video-upscaler)
• Local stdio via npm (`videoupscaler-mcp`): npx -y videoupscaler-mcp with VIDEOUPSCALER_API_KEY (npm package)

{

"mcpServers": { "videoupscaler": { "command": "npx", "args": ["-y", "videoupscaler-mcp"], "env": { "VIDEOUPSCALER_API_KEY": "vu_live_..." } } } }

Most clients connect by signing in: add the URL, a browser window opens, you sign in to VideoUpscaler and click Allow. Clients that can't sign in use an API key from Settings → API Keys.

Claude (claude.ai and the desktop app)

Open Settings → Connectors → Add custom connector, enter https://videoupscaler.co/api/mcp, click Connect, then sign in and allow access.

Claude Code

claude mcp add --transport http videoupscaler https://videoupscaler.co/api/mcp --scope user

Then run /mcp, select videoupscaler and choose Authenticate. To use an API key instead, add --header "Authorization: Bearer $VIDEOUPSCALER_API_KEY".

Cursor (API key)

Add to ~/.cursor/mcp.json (example file):

{

"mcpServers": { "videoupscaler": { "url": "https://videoupscaler.co/api/mcp", "headers": { "Authorization": "Bearer ${env:VIDEOUPSCALER_API_KEY}" } } } }

</details>

VS Code

Add to .vscode/mcp.json (example file). VS Code asks you to sign in the first time:

{

"servers": { "videoupscaler": { "type": "http", "url": "https://videoupscaler.co/api/mcp" } } }

</details>

Other clients

Any client that supports remote MCP servers over Streamable HTTP works. Clients that support MCP authorization sign in automatically; others send the header Authorization: Bearer .

Tools

Try asking

• "How many VideoUpscaler credits do I have left?"
• "Upscale https://example.com/clip.mp4 to 4K and give me the link when it's done."
• "Upscale ./intro.mp4 to 2K." (clients that can run commands upload the file with create_upload first)

3. REST API (for developers)

Best for: apps, scripts and pipelines that upscale videos automatically.

1. Buy any credit pack on the pricing page (this unlocks the API for good).
2. Create a key in Settings → API Keys and store it as VIDEOUPSCALER_API_KEY.
3. Start an upscale, then poll the task until it's completed:

curl https://videoupscaler.co/api/v1/upscale \

-H "Authorization: Bearer $VIDEOUPSCALER_API_KEY" \ -H "Content-Type: application/json" \ -H "Idempotency-Key: my-first-upscale" \ -d '{"video_url": "https://example.com/clip.mp4", "resolution": "2k"}'

curl https://videoupscaler.co/api/v1/tasks/TASK_ID \

-H "Authorization: Bearer $VIDEOUPSCALER_API_KEY"

-> "status": "completed", "output_url": "https://..."

Full examples: curl · Node.js · Python. Machine-readable spec: openapi.yaml. Reference: videoupscaler.co/docs.

Videos that aren't online yet: call POST /api/v1/uploads, PUT the file to the returned upload_url, then pass the returned video_url to /upscale (see the Node.js example).

4. Workflow Automation & n8n Integration

Best for: no-code/low-code media pipelines in n8n, Make.com, and Zapier (e.g., automatically upscaling AI-generated clips from Sora, Runway, Kling, or Veo to 4K before publishing to YouTube, TikTok, or Google Drive).

• Official n8n Community Node: n8n-nodes-videoupscaler (GitHub repository)
• Install in self-hosted n8n via Settings → Community Nodes → Install → n8n-nodes-videoupscaler
• Ready-to-Import Workflow Templates (browse in examples/workflows/):
• n8n-videoupscaler-workflow.json — Self-documenting zero-install HTTP Request + server-side long-polling (?wait=45) workflow (works on both n8n Cloud & self-hosted)
• n8n-videoupscaler-webhook-workflow.json — Zero-polling async webhook callback pipeline (X-VideoUpscaler-Event: task.completed)
• n8n-videoupscaler-node-workflow.json — 3-node pipeline using the official n8n-nodes-videoupscaler community node
• make-videoupscaler-blueprint.json — Make.com 2-module scenario blueprint
• Documentation & Guides:
• Integrations Hub (videoupscaler.co/integrations)
• Workflow Automation Guide (videoupscaler.co/docs/workflows)

The AI model

VideoUpscaler runs [FlashVSR](https://github.com/OpenImagingLab/FlashVSR), a diffusion-based video super-resolution model (CVPR 2026, Apache-2.0).

| Why this model | Diffusion models generate realistic texture (skin, hair, foliage, fabric) instead of the smooth, plastic loo