A secure 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.
curl -fsSL https://raw.githubusercontent.com/Automata-Labs-team/code-sandbox-mcp/main/install.sh | bash
# Run in PowerShell
irm https://raw.githubusercontent.com/Automata-Labs-team/code-sandbox-mcp/main/install.ps1 | iex
The installer will: 1. Check for Docker installation 2. Download the appropriate binary for your system 3. Create necessary configuration files
bash
chmod +x code-sandbox-mcpsandbox_initializeInitialize a new compute environment for code execution. Creates a container based on the specified Docker image.
Parameters:
- image (string, optional): Docker image to use as the base environment
- Default: 'python:3.12-slim-bookworm'
Returns:
- container_id that can be used with other tools to interact with this environment
copy_projectCopy a directory to the sandboxed filesystem.
Parameters:
- container_id (string, required): ID of the container returned from the initialize call
- local_src_dir (string, required): Path to a directory in the local file system
- dest_dir (string, optional): Path to save the src directory in the sandbox environment
write_fileWrite a file to the sandboxed filesystem.
Parameters:
- container_id (string, required): ID of the container returned from the initialize call
- file_name (string, required): Name of the file to create
- file_contents (string, required): Contents to write to the file
- dest_dir (string, optional): Directory to create the file in (Default: ${WORKDIR})
sandbox_execExecute commands in the sandboxed environment.
Parameters:
- container_id (string, required): ID of the container returned from the initialize call
- commands (array, required): List of command(s) to run in the sandboxed environment
- Example: ["apt-get update", "pip install numpy", "python script.py"]
copy_fileCopy a single file to the sandboxed filesystem.
Parameters:
- container_id (string, required): ID of the container returned from the initialize call
- local_src_file (string, required): Path to a file in the local file system
- dest_path (string, optional): Path to save the file in the sandbox environment
sandbox_stopStop and remove a running container sandbox.
Parameters:
- container_id (string, required): ID of the container to stop and remove
Description: Gracefully stops the specified container with a 10-second timeout and removes it along with its volumes.
A dynamic resource that provides access to container logs.
Resource Path: containers://{id}/logs
MIME Type: text/plain
Description: Returns all container logs from the specified container as a single text resource.
The installer automatically creates the configuration file. If you need to manually configure it:
// ~/.config/Claude/claude_desktop_config.json
{
"mcpServers": {
"code-sandbox-mcp": {
"command": "/path/to/code-sandbox-mcp",
"args": [],
"env": {}
}
}
}
// ~/Library/Application Support/Claude/claude_desktop_config.json
{
"mcpServers": {
"code-sandbox-mcp": {
"command": "/path/to/code-sandbox-mcp",
"args": [],
"env": {}
}
}
}
// %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"code-sandbox-mcp": {
"command": "C:\\path\\to\\code-sandbox-mcp.exe",
"args": [],
"env": {}
}
}
}
For other AI applications that support MCP servers, configure them to use the code-sandbox-mcp binary as their code execution backend.
If you want to build the project locally or contribute to its development, see DEVELOPMENT.md.
This project is licensed under the MIT License - see the LICENSE file for details.
$ claude mcp add code-sandbox-mcp \
-- python -m otcore.mcp_server <graph>