What prerequisites are needed to run Code Sandbox MCP 🐳?
Docker must be installed and running on your system. The server works on Linux, macOS, and Windows.
@Automata-Labs-team
Basic information
An MCP server to create secure code sandbox environment for executing code within Docker containers. This MCP server provides AI applications with a safe and isolated environment for running code while maintaining security through containerization.
No standard config provided
This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.
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Code Sandbox MCP 🐳 is a secure sandbox environment for executing code within Docker containers. It provides AI applications with a safe, isolated runtime for running code, leveraging containerization to maintain security.
Install via the quick install script (Linux/macOS: curl -fsSL https://raw.githubusercontent.com/Automata-Labs-team/code-sandbox-mcp/main/install.sh | bash; Windows: irm ... | iex), or download the binary manually. Then configure your MCP‑compatible AI application (e.g., Claude Desktop) to point to the code-sandbox-mcp executable. Use tools like sandbox_initialize, sandbox_exec, copy_project, write_file, copy_file, and sandbox_stop to manage containers and execute code.
Docker must be installed and running on your system. The server works on Linux, macOS, and Windows.
Use the quick‑install script for your platform, or download the latest release binary from the GitHub releases page and place it in your PATH.
The installer automatically creates the configuration file. For manual setup, add an entry in your Claude Desktop config file (e.g., `~/.config/Claude/claude_desktop_config.json` on Linux) with the path to the `code-sandbox-mcp` binary.
The server provides tools to initialize a container (`sandbox_initialize`), copy files/directories (`copy_project`, `copy_file`, `write_file`), execute commands (`sandbox_exec`), stop and remove a container (`sandbox_stop`), and a resource to retrieve container logs (`containers://{id}/logs`).
It uses Docker containers for isolated execution, applies resource limitations through Docker constraints, and separates stdout and stderr streams.

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