n8n Custom Exec Node

🎯 Why This Node?

n8n v2 removed the built-in Execute Command node for security reasons, leaving many users unable to:

• Process media files with FFmpeg
• Run shell scripts for data transformation
• Execute command-line tools in workflows
• Integrate with system utilities

This custom node brings back that power in a controlled, Docker-isolated environment with modern templating support.

✨ Features

• 🚀 Execute Any Bash Command - Run shell commands directly in your n8n container
• 📝 Full Templating Support - Use {{ $json.field }} to inject dynamic data from your workflow
• ⚙️ Environment Variables - Securely pass sensitive data without hardcoding
• ⏱️ Configurable Timeouts - Set execution limits to prevent hanging processes
• 🔒 Error Handling - Optional ignore-errors mode for fault-tolerant workflows
• 📊 Detailed Output - Capture stdout, stderr, and exit codes
• 🎬 FFmpeg Ready - Perfect for media processing workflows
• 🐳 Docker Isolated - Runs safely inside your n8n container

📦 Installation

npm (Recommended)

npm install n8n-nodes-custom-exec

Then restart n8n. The node will appear as "Custom Exec" in your node panel.

Docker Volume Mount

volumes:
  - ./n8n-nodes-custom-exec/dist:/home/node/.n8n/custom

See Installation Guide for detailed setup instructions.

🚀 Quick Start

1. Basic Example

Input JSON:

{
  "name": "World",
  "count": 42
}

Command:

echo "Hello {{ $json.name }}! Count: {{ $json.count }}"

Output:

{
  "name": "World",
  "count": 42,
  "exec": {
    "command": "echo \"Hello World! Count: 42\"",
    "exitCode": 0,
    "output": "Hello World! Count: 42\n"
  }
}

2. FFmpeg Media Processing

Transform images with dynamic text overlays:

Input:

{
  "filename": "product-001",
  "title": "SALE 50% OFF",
  "slug": "sale-50-off"
}

Command:

ffmpeg -i /home/node/input/{{ $json.filename }}.png \
  -vf "drawtext=text='{{ $json.title }}':fontfile=/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf:fontsize=70:fontcolor=#FFDE21:x=(w-text_w)/2:y=(h-text_h)/2" \
  /home/node/output/{{ $json.slug }}.webp

3. File Processing

Command:

# Create directory and process files
mkdir -p /home/node/output/{{ $json.slug }} && \
  convert {{ $json.image }} -resize 800x600 /home/node/output/{{ $json.slug }}/thumb.jpg && \
  echo "Processed {{ $json.filename }}" > /home/node/output/{{ $json.slug }}/status.txt

📚 Documentation

Comprehensive guides for every use case:

Getting Started

• Quick Start Guide - Get running in 5 minutes
• Installation Instructions - Detailed setup for Docker and npm
• Project Overview - Architecture and design decisions

Using the Node

• Usage Examples - Real-world command examples
  • FFmpeg media processing
  • Image manipulation
  • File operations
  • Data transformation
  • Python scripts
  • Batch processing

Development & Publishing

• Publishing Guide - How to publish to npm
• Release Checklist - Quick reference for releases
• Setup Complete - GitHub Actions configuration

💡 Examples

Batch Image Conversion

for file in /home/node/input/*.jpg; do
  filename=$(basename "$file" .jpg)
  ffmpeg -i "$file" -quality 85 "/home/node/output/${filename}.webp"
done

CSV to JSON

python3 -c "import csv, json; \
  data = list(csv.DictReader(open('/home/node/data/{{ $json.csvFile }}.csv'))); \
  json.dump(data, open('/home/node/output/{{ $json.outputName }}.json', 'w'), indent=2)"

PDF Generation

echo "<h1>{{ $json.title }}</h1><p>{{ $json.content }}</p>" | \
  wkhtmltopdf - /home/node/pdfs/{{ $json.filename }}.pdf

Conditional Processing

if [ "{{ $json.type }}" = "video" ]; then
  ffmpeg -i /home/node/input/{{ $json.file }} -vf scale=1280:720 /home/node/output/{{ $json.file }}
else
  cp /home/node/input/{{ $json.file }} /home/node/output/
fi

See Usage Examples for 20+ more examples.

🎬 Use Cases

Perfect for n8n users who need:

Media Processing

• Add watermarks to images
• Convert video formats
• Extract audio from video
• Generate thumbnails
• Batch resize images

Data Transformation

• CSV/JSON conversion
• PDF generation
• File compression
• Format transformations
• Data validation

System Automation

• File management
• Backup operations
• Log processing
• Cleanup tasks
• Monitoring scripts

Integration

• Call external APIs with curl
• Run Python/Ruby scripts
• Execute custom tools
• Process command output
• Chain multiple commands

⚙️ Configuration

Setting	Default	Description
Command	-	Bash command to execute
Working Directory	/home/node	Command execution directory
Timeout	60000ms	Maximum execution time
Ignore Errors	false	Continue workflow on command failure
Environment Variables	-	Custom env vars for the command
Return Full Output	false	Include both stdout and stderr

🔒 Security

• Runs inside Docker container (isolated environment)
• No network access by default
• Configurable timeout prevents infinite loops
• Use environment variables for secrets
• Validate user input before passing to commands

🛠️ Development

Build from Source

git clone https://github.com/shadow-software/n8n-nodes-custom-exec-node.git
cd n8n-nodes-custom-exec-node
npm install
npm run build

Test Locally

npm run docker:start
# Open http://localhost:5678
# Search for "Custom Exec" node

Helpful Scripts

npm run build          # Build TypeScript
npm run dev            # Watch mode
npm run docker:start   # Start n8n
npm run docker:logs    # View logs
npm run docker:ffmpeg  # Start with FFmpeg installed

📦 Package Info

• Package Name: n8n-nodes-custom-exec
• Repository: github.com/shadow-software/n8n-nodes-custom-exec-node
• npm Registry: npmjs.com/package/n8n-nodes-custom-exec
• License: MIT
• Size: ~5 KB (minified)

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

📝 Changelog

v1.0.0 (2025-12-17)

• Initial release
• Execute bash commands with templating
• Environment variable support
• Configurable timeout and error handling
• Full stdout/stderr capture

💬 Support

• Issues: GitHub Issues
• Email: hello@shadowsoftware.com
• Website: shadowsoftware.com

🌟 Show Your Support

If this node helped you, please give it a ⭐️ on GitHub!

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📄 License

MIT License - see LICENSE file for details.

Copyright © 2025 Shadow Software LLC