Terminal Server

This project provides multiple examples of MCP server setup, supports local and cloud deployment, includes two transport modes: STDIO and SSE, and is accompanied by detailed tutorial videos.

Developer tools Operating system automation #AI Protocol #Model Service #Terminal Control #Cloud Deployment .Python

rating : 2.5 points

downloads : 9.5K

update time : 2025-04-28

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What is an MCP server?

The MCP server is a bridge that allows AI assistants (such as Claude) to perform actual operations. It enables AI to access the local environment, run commands, and process files, as if the AI has 'hands' to operate the computer.

How to use an MCP server?

You only need to start the server and then send natural language instructions through the AI interface. The server will securely execute these instructions and return the results.

Use cases

Scenarios that require AI to interact with the actual system, such as automating daily tasks, file processing, development assistance, and data analysis pre - processing.

Main Features

Data Storage

AI can store and retrieve data such as files and API responses.

Tool Execution

AI can run predefined tools and functions.

Prompt Templates

Use preset task templates to improve efficiency.

Multiple Transport Modes

Supports two communication protocols: STDIO and SSE.

Advantages

Enable AI to have actual operation capabilities

Flexible deployment options (local/Docker/cloud)

Simple natural language interaction

Scalable functional modules

Limitations

Need to carefully manage permissions to prevent security risks

Currently does not support the Windows system

Performance depends on the local environment configuration

How to Use

Choose a Deployment Method

Choose local Python, Docker, or cloud deployment according to your needs.

Start the Server

Run the corresponding startup command.

Connect to the AI Interface

Enter instructions in the AI interface such as Claude.

Usage Examples

File Management

Let AI help organize the working directory.

System Information

Get server system information.

Frequently Asked Questions

Is the MCP server secure?

Which AI models are supported?

Can custom functions be extended?

Related Resources

Local Python Setup Tutorial

How to run the MCP server locally.

Docker Deployment Tutorial

Use Docker containers for deployment.

SSE Server Tutorial

Set up an MCP server for SSE communication.

GitHub Repository

Source code and examples.

🚀 MCP Server and Standard Input/Output Server Examples

This repository provides multiple examples for setting up MCP servers. MCP (Model Context Protocol) is a framework that allows AI models to store data, run tools, and complete specific tasks using prompts.

🚀 Quick Start

Welcome to the The AI Language project! In this repository, you'll find multiple examples of setting up MCP servers. MCP (Model Context Protocol) is a framework that allows AI models to store data, run tools, and complete specific tasks using prompts.

✨ Available Server Examples

We offer four examples to help you set up MCP servers in different environments. The following table summarizes each configuration:

Example	Server Type	Transmission Method	Environment	Docker	Tutorial Link
1	Terminal Server (Standard Input/Output)	Standard Input/Output	Local	No	Tutorial 1
2	Terminal Server (Standard Input/Output)	Standard Input/Output	Local	Yes	Tutorial 2
3	Terminal Server (SSE)	SSE	Local	Yes	Tutorial 3
4	Terminal Server (SSE)	SSE	Google Cloud Platform (Web)	Yes	Tutorial 3

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📚 What is MCP?

MCP (Model Context Protocol) is a protocol that allows AI models to:

Store data (e.g., files or API responses)
Run tools (functions that AI can execute)
Use prompts (pre - defined templates for specific tasks)

📦 Installation Options

Option 1: Local Setup without Docker

This option demonstrates how to set up an MCP server locally using Python without Docker. Please refer to the video tutorial: Tutorial 1

Option 2: Setup with Docker

This option shows how to containerize and run an MCP server using Docker. Please refer to the video tutorial: Tutorial 2

Option 3: Use with SSE (Local, Docker)

This option demonstrates how to run an MCP server with SSE in a local environment using Docker. Please refer to the video tutorial: Tutorial 3

Option 4: Setup with SSE on Google Cloud Platform (GCP)

This option details how to deploy an SSE server to Google Cloud Platform (GCP) using Docker. Please refer to the video tutorial: Tutorial 3

💻 Testing the MCP Server

Once the server is running, you can test it by using prompts in Claude, for example:

Run the ls command in my workspace.
Execute echo Hello from Claude.

You should see the output directly from the terminal server 🎉

🔍 Summary

Congratulations! You've successfully built an MCP server that can execute terminal commands. You can run it locally or in Docker, depending on your preference.

Next Steps:

Add security checks to block potentially dangerous commands.
Allow Claude to read and write files.
Connect the server to a cloud system or a remote environment.

For any questions or suggestions for improvement, feel free to submit an issue or a pull request in this repository!

🤝 Contribution

Currently, this project does not accept external code contributions.

This is to keep the license simple and avoid any shared copyright.

You are very welcome to: ✅ Report bugs or request features (via GitHub issues)
✅ Fork the repository and work on your branch
✅ Submit a pull request to help improve it