4/17/2025

Setup Guide for Hosting Your MCP Server on Cloud Provider

In this digital age, hosting your Model Context Protocol (MCP) server in the cloud has never been more accessible or beneficial. As developers and businesses alike strive for flexibility, scalability, and reliability, cloud hosting solutions have become the backbone of modern infrastructure. This guide will walk you through the detailed steps necessary to set up your MCP server on a cloud platform, ensuring you have all the tools and knowledge needed to connect and manage your AI-driven applications effectively.

What is MCP?

The Model Context Protocol, known as MCP, is an open protocol that standardizes interactions between AI models and numerous data sources. It facilitates a streamlined connection for developers looking to harness the power of AI without the intricacies of local setups. When powered by a cloud service, your MCP server can interface with remote resources far beyond any classic desktop setup.

Why Use a Cloud Provider?

Scalability: Need more resources? Just scale up. You won’t have to worry about purchasing new hardware.
Accessibility: Your server can be reached from anywhere in the world, making remote work seamless.
Cost-Effectiveness: Pay-as-you-go models let you only pay for what you use.
Maintenance: Cloud service providers handle the heavy lifting regarding updates and security setups.

Choosing a Cloud Provider

Before diving into the setup, you need to select a cloud provider that suits your needs. Popular options include AWS, Azure, and Google Cloud Platform (GCP). For this guide, we'll focus primarily on DigitalOcean, a popular choice for its simplicity, especially for beginners.

Setting Up Your Cloud Account

Create an Account: First, visit DigitalOcean and sign up for an account if you haven’t already done so.
Billing: You’ll need to enter your billing details. However, they often have promotions for new users, so look out for any available credits.

Creating a Virtual Machine (Droplet)

Login to your DigitalOcean dashboard.
Click on the “Create” button and select Droplets.
Choose an Operating System: For this guide, you can choose Ubuntu 20.04 LTS, ideal for hosting web applications.
Select a Plan: Pick a plan based on your usage. The regular plan works great for small to medium-sized applications. Choose a plan with at least 2 GB of RAM and 1 CPU, which should be sufficient for running an MCP server. This can be scaled later on as needed.
Select Data Center Region: Choose a location that is closest to your target audience for minimal latency.
Finalize Options: Add SSH keys for secure access if you desire a more secure method than passwords. You can generate a key pair using PuTTY or any terminal on macOS or Linux using
1ssh-keygen
.
Click on Create Droplet! Wait for a few moments, and your Virtual Machine will be ready for access.

Connect to Your Droplet

Using SSH

Open your terminal. If you're on Windows, you can use PuTTY to connect to your droplet.
For SSH, the command is:
1 2bash ssh root@your_droplet_ip
If you’re prompted for a password, it’s the root password set during the droplet creation.

First Steps on Your Droplet

Once you're in, update your packages:

1
2

bash
apt update && apt upgrade -y

This ensures you’re working with the latest versions of software.

Set Up Java

Since the MCP server requires Java, you can install it using:

1
2

bash
apt install openjdk-11-jdk -y

You can verify the installation using:

1
2

bash
java -version

Installing MCP

Clone the MCP repository from GitHub:
1 2 3bash git clone https://github.com/modelcontextprotocol/servers.git cd servers
Install Dependencies: While the precise dependencies will vary, using npm to install most packages helps maintain compatibility:
1 2bash npm install

Configuring the MCP Server

The configuration process might differ based on your needs. Follow these steps:

Navigate to your MCP server folder:
1 2bash cd mcp-server
Create a configuration file (e.g.,
1config.json
) tailored to your server's requirements. Specify details such as API keys, database connections, etc., so MCP can seamlessly integrate with external data sources.

Running Your MCP Server

To launch your server, run the command:

1
2

bash
npm start

This will initialize your MCP server and get it up and running in the cloud.

Setting Up Remote Access

Now that your MCP server is running, configure your firewall to allow external access:

Using UFW (Uncomplicated Firewall)

If UFW is not installed, you can do so:
1 2bash apt install ufw
Allow traffic on your server port (default may be
18080
or another specified port in your configuration):
1 2 3bash ufw allow 8080 ufw enable
Check the status of your firewall to confirm the rules:
1 2bash ufw status

Conclusion

With your MCP server running in the cloud, you are now equipped to handle various tasks through your cloud-based AI applications. The implications of having a reliable, scalable server are vast, allowing for increased data handling and AI-driven decision-making processes.

As your needs grow, consider switching to more robust cloud solutions or optimizing your current setup to support a larger user base or more complex applications.

Enhance Your MCP Experience with Arsturn

To further explore the depths of AI capabilities, consider integrating your MCP server with a custom chatbot using Arsturn. With Arsturn, you can instantly create engaging ChatGPT chatbots tailored to your needs without any coding experience. Just imagine a customer service AI that beautifully connects with your audience while boosting engagement & conversions effortlessly.

Take advantage of Arsturn's no-code chatbot builder, which makes it easy to train bots with your own data. So, whether you’re an influencer, small business, or just diving into the world of AI, Arsturn has the tools you need! Claim your free chatbot today.

The future is conversational AI, and Arsturn is your passport into this exciting world of unlimited possibilities!