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MCP server for terminal commands
This repo provides example MCP servers that let a connected agent execute terminal commands. It includes STDIO and SSE variants, with Docker-based setup options and a Claude Desktop configuration file.
Videos about this repo
Builders who want an MCP server that can run shell commands from Claude Desktop or another MCP client.
You can let an agent execute commands like `ls` or `echo` in your terminal instead of copying them by hand.
What it does
STDIO terminal server
A local MCP server example that speaks over STDIO for terminal command execution.
SSE terminal server
A server variant that exposes the same idea over SSE for local or web deployment.
Docker setup
Dockerfiles for running the server locally or as a containerized service.
Claude Desktop config
A `claude_desktop_config.json` file for wiring the server into Claude Desktop.
README
MCP SSE Server and STDIO Server Examples
Introduction
Welcome to The AI Language project! In this repository, you'll find multiple examples of setting up MCP Servers. MCP (Model Context Protocol) is a framework for AI models that enables them to store data, run tools, and use prompts for specific tasks.
Available Server Examples
We provide four examples to help you set up your MCP server in different environments. The table below summarizes each configuration:
| Example | Server Type | Transport Method | Environment | Docker | Tutorial Link |
|---|---|---|---|---|---|
| 1 | Terminal Server (STDIO) | STDIO | Local | No | Tutorial 1 |
| 2 | Terminal Server (STDIO) | STDIO | 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 (like files or API responses)
- Run tools (functions that AI can execute)
- Use prompts (predefined templates for tasks)
Option 1: Setup Without Docker (Local Python)
This option demonstrates how to set up an MCP server locally using Python without Docker. Follow the video tutorial: Tutorial 1
Option 2: Setup With Docker
This option shows how to containerize the MCP server with Docker and run it locally. Follow the video tutorial: Tutorial 2
Option 3: Setup with SSE (Local, Docker)
This option demonstrates how to run an MCP server over SSE using Docker in a local environment. Follow the video tutorial: Tutorial 3
Option 4: Setup with SSE on Google Cloud Platform
This option details how to deploy the SSE server to Google Cloud Platform using Docker. Follow the video tutorial: Tutorial 3
Testing the MCP Server
Once the server is running, you can test it by using prompts in Claude, such as:
Run the command ls in my workspace.Execute echo Hello from Claude.
You should see the output directly from your terminal server 🎉
Wrapping Up
Congrats! 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 cloud systems or remote environments.
For any issues or improvements, feel free to contribute and open an issue or pull request in this repository!
🤝 Contributing
At this time, this project does not accept external code contributions.
This is to keep licensing simple and avoid any shared copyright.
You're very welcome to:
✅ Report bugs or request features (via GitHub Issues)
✅ Fork the repo and build your own version
✅ Suggest documentation improvements
If you'd like to collaborate in another way, feel free to open a discussion!
Files in the repo
- sse_server
- streamable_http_server
- .gitignore
- .python-version
- claude_desktop_config.json
- Dockerfile
- LICENSE.txt
- main.py
- pyproject.toml
- README.md
- requirements.txt
- terminal_server.py
- uv.lock
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