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Step-by-Step: Deploying NCA Toolkit with Docker on GCP, Hostinger & Local

Publish Date: August 14, 2025
Written by: editor@delizen.studio
Comment: 0

A person using a laptop to deploy the NCA Toolkit with Docker

Deploying NCA Toolkit with Docker on GCP, Hostinger & Local: A Comprehensive Guide

The NCA (Nifty Collection Assistant) Toolkit is a powerful application that can help you manage your collections of any kind. With the rise of Docker, deploying the NCA Toolkit has become more accessible than ever. In this guide, we will walk you through deploying the NCA Toolkit with Docker on Google Cloud Platform (GCP), Hostinger, and your local machine.

Prerequisites

Before we begin, make sure you have the following:

  • A Docker installed on your local machine
  • A Google Cloud Platform account
  • A Hostinger account

Deploying NCA Toolkit with Docker on GCP

Follow these steps to deploy the NCA Toolkit on GCP:

  1. Create a new GCP project.
  2. Enable the Compute Engine API.
  3. Create a new Compute Engine instance.
  4. SSH into the instance and install Docker.
  5. Pull the NCA Toolkit Docker image.
  6. Run the NCA Toolkit container.

Deploying NCA Toolkit with Docker on Hostinger

Follow these steps to deploy the NCA Toolkit on Hostinger:

  1. Log in to your Hostinger account.
  2. Create a new VPS.
  3. SSH into the VPS and install Docker.
  4. Pull the NCA Toolkit Docker image.
  5. Run the NCA Toolkit container.

Deploying NCA Toolkit with Docker Locally

Follow these steps to deploy the NCA Toolkit locally:

  1. Open your terminal.
  2. Install Docker.
  3. Pull the NCA Toolkit Docker image.
  4. Run the NCA Toolkit container.

Conclusion

Deploying the NCA Toolkit with Docker is a straightforward process, whether you’re using GCP, Hostinger, or your local machine. With this guide, you can now deploy the NCA Toolkit and start managing your collections with ease.

For recommended tools, see Recommended tool

Disclosure: We earn commissions if you purchase through our links. We only recommend tools tested in our AI workflows.

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