How to Generate Video with Cursor: Adding Video Generation to Your Agent Workflow

Cursor handles code generation exceptionally well. But video? There's no built-in command for it, no /generate-video shortcut, and no way to produce an MP4 or WebM directly from the Composer.

Cursor cannot generate video natively. It has no connection to video generation models like Veo, Sora, Kling, or Seedance. If you need video as part of a development workflow—demo clips, product previews, documentation animations, or AI-generated content—you'll need to add that capability externally.

This guide covers why video generation matters in modern development workflows, how Cursor's limitations apply, and how to add production-ready video generation to any Cursor agent using AnyCap CLI.

Why Developers Need Video Generation in Their Workflows

The use cases are more common than they sound.

Product demos and feature walkthroughs — SaaS teams need short video clips to accompany feature launches. Generating a polished 10-second product demo from a prompt is dramatically faster than recording, editing, and exporting manually.

AI-generated content pipelines — If you're building a blog, social media scheduler, or marketing automation tool, having agents generate matching video content (alongside text and images) creates complete multimedia outputs.

Documentation and onboarding — Animated explainers and step-by-step walkthroughs are more effective than static screenshots. Generating these from scripts rather than recording them manually scales better across a product.

Prototyping and visualization — Agents that generate data reports or dashboards can include video summaries—timelapse animations, chart transitions, or ambient B-roll—that make outputs more engaging.

What Cursor Can and Cannot Do with Video

Cursor can:

• Write code that calls video generation APIs (Replicate, RunwayML, etc.)
• Generate code for video processing with FFmpeg, MoviePy, or OpenCV
• Describe what a video should contain
• Analyze video files you share in the chat (if using a vision-capable model)

Cursor cannot:

• Directly invoke video generation models
• Produce an MP4 or WebM as output without you manually running the generated code
• Run video generation pipelines end-to-end without external API credentials and custom setup

The gap is consistent: Cursor's AI models are language and vision models. They produce text and understand images. Video generation is an entirely separate pipeline that requires models like Veo, Kling, or Seedance—none of which are available through the Cursor interface.

Adding Video Generation with AnyCap CLI

AnyCap provides video generation as a command-line tool that Cursor agents can invoke directly. One command, one credential, multiple models.

Install once:

curl -fsSL https://anycap.ai/install.sh | sh
anycap login

Generate a video:

anycap video generate \
  --model veo-3.1 \
  --prompt "A developer's screen showing code being written in real time, dark mode terminal, clean and modern, professional" \
  -o product-demo.mp4

The video downloads to your working directory when generation completes. No API key management, no model hosting required.

Available Video Models

Check the current model list:

anycap video models

As of mid-2026, the lineup includes:

For product demos and UI animations, veo-3.1 produces the most polished results. For longer narrative clips, seedance-1.5-pro maintains subject consistency better across frames.

Practical Workflows

Workflow 1: Ask Cursor's Composer to Generate a Video

Once AnyCap is installed, instruct Cursor's agent directly in the Composer:

Generate a 5-second product demo video for our analytics dashboard.
Use AnyCap CLI with veo-3.1.
The video should show a sleek dark-mode dashboard with animated charts.
Save as dashboard-demo.mp4.

Cursor's agent will construct and run:

anycap video generate \
  --model veo-3.1 \
  --prompt "Sleek dark-mode analytics dashboard with animated bar charts and line graphs, smooth transitions, professional product demo style, 5 seconds" \
  -o dashboard-demo.mp4

The video saves to your project directory. No switching apps required.

Workflow 2: Image-to-Video from a Screenshot or Mockup

Already have a mockup or screenshot? AnyCap supports image-to-video mode—animate a static image into a short clip:

# Check which modes a model supports
anycap video models seedance-1.5-pro | jq -r '.model.operations[].modes[].mode'

# Generate video from an existing image
anycap video generate \
  --model seedance-1.5-pro \
  --mode image-to-video \
  --param images=./dashboard-screenshot.png \
  --prompt "Smooth zoom in, data charts animating, professional product feel" \
  -o dashboard-animated.mp4

This workflow is particularly useful for design reviews—you can show stakeholders an animated version of a static design without manual animation work.

Workflow 3: Batch Video Generation in a Script

For content pipelines that need multiple videos:

import subprocess
import json

def generate_video(prompt: str, output: str, model: str = "veo-3.1") -> str:
    result = subprocess.run(
        [
            "anycap", "video", "generate",
            "--model", model,
            "--prompt", prompt,
            "-o", output
        ],
        capture_output=True,
        text=True
    )
    data = json.loads(result.stdout)
    return data["local_path"]

# Generate demo videos for product feature announcements
features = [
    ("AI-powered search with instant results, sleek UI", "search-feature.mp4"),
    ("Dashboard with real-time analytics, data streaming in", "analytics-feature.mp4"),
    ("User onboarding flow, clean walkthrough animation", "onboarding-feature.mp4"),
]

for prompt, filename in features:
    path = generate_video(prompt, filename)
    print(f"Generated: {path}")

Cursor's AI can write, debug, and iterate on this script entirely within the editor.

Integrating into Cursor Rules

Add video generation to your .cursor/rules/ directory so agents have it available automatically:

# .cursor/rules/anycap.mdc

## Video Generation
When the user asks to generate a video or animation, use AnyCap CLI:
- Command: anycap video generate --model veo-3.1 --prompt "..." -o filename.mp4
- For cinematic quality: --model veo-3.1
- For character consistency: --model seedance-1.5-pro  
- For image-to-video: add --mode image-to-video --param images=./source.png
- Always save with .mp4 extension and a descriptive filename
- Videos generate in 60-90 seconds — run in background for long batches
- Check available models: anycap video models

Once the rule is in place, "generate a demo video for this feature" is a valid instruction without further tool specification.

Cursor vs. Other AI Coding Tools for Video Generation

Video generation is uniformly absent from AI coding tools as of mid-2026. The gap makes sense—these tools optimize for code, not multimedia pipelines. Adding it via a CLI tool is the practical path for any of them.

Limitations to Know

Generation takes time. Video generation runs 60-120 seconds depending on the model. For agent workflows that need to produce multiple videos, run generation commands in the background or plan for the latency.

Output duration is short. Most models produce 5-10 second clips. For longer videos, you'll need to chain multiple clips together using FFmpeg or a video editing pipeline.

Prompt quality determines output quality. Vague prompts produce generic results. Include specifics: camera movement, style references, color palette, action description, and pacing.

Credit usage is higher than images. Video generation consumes significantly more credits than image generation. Check your credit balance before batch runs.

Getting Started

# 1. Install AnyCap
curl -fsSL https://anycap.ai/install.sh | sh

# 2. Log in
anycap login

# 3. Check available video models
anycap video models | jq -r '.models[].model'

# 4. Generate a test video
anycap video generate \
  --model veo-3.1 \
  --prompt "Abstract blue geometric animation, clean and minimal, 5 seconds" \
  -o test-video.mp4

# 5. Open to review
open test-video.mp4      # macOS
xdg-open test-video.mp4  # Linux

From that foundation, your Cursor agents can generate video as part of any workflow—product demos, content pipelines, documentation animations—without leaving the editor or manually managing video model APIs.

Frequently Asked Questions

Does video generation work in Cursor background agents? Yes. Background agents can run shell commands. As long as AnyCap is installed in the environment, background agents can invoke anycap video generate as part of any automated workflow.

Can I control video length? Duration depends on the model. Most models support a duration parameter. Run anycap video models <model-name> schema to see what parameters a specific model accepts before generating.

What video formats does AnyCap output? MP4 by default. Some models also support WebM. Specify the extension in your -o flag (-o output.webm).

Can I generate video from text describing UI interactions? Yes—describe the UI state, transitions, and actions in the prompt. For best results, also provide a reference screenshot of the UI using image-to-video mode.

How do I chain multiple clips into a longer video? Generate individual clips with AnyCap, then use FFmpeg to concatenate: ffmpeg -f concat -safe 0 -i clips.txt -c copy final.mp4. Cursor's AI can write the FFmpeg pipeline for you once you have the source clips.