Cloud Sandbox MCP
Allows pushing code to GitHub repositories via a dedicated audited MCP tool. Requires a GitHub token.
Provides local Kubernetes tooling and persistent kubeconfig for managing Kubernetes clusters.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Cloud Sandbox MCPSet up a Python project and run tests"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Cloud Sandbox MCP 0.2.0 — Workstation Mode
A private MCP server that gives ChatGPT a persistent, VM-like Linux engineering workstation inside Docker.
Each workspace has:
root access and
apt-get;Node.js 22, npm/corepack, Python 3, pip/venv, and
uv;Chromium and Playwright-compatible browser runtime;
a private nested Docker daemon with Docker Compose;
persistent repository, home directory, caches, cloud CLI configuration, and nested Docker state;
Git operations, tests, builds, services, databases, and local Kubernetes tooling through the terminal;
no host Docker socket inside the workstation.
The outer MCP controller still uses the host Docker socket to create and manage workstation containers. The workstation receives a private Docker daemon, not the host socket.
Upgrade from 0.1.x
cd ~/Downloads
unzip cloud-sandbox-mcp-v0.2.0-workstation.zip
cd cloud-sandbox-mcp-v0.2.0-workstation
cp ../cloud-sandbox-mcp-v0.1.3/.env .env
./scripts/setup.sh
./scripts/upgrade-workspaces.shThe upgrade script preserves every workspace's:
repo/home/new
docker/data directory
It replaces only the runtime container.
Related MCP server: mcp-docker-agentic
Verify the workstation
From ChatGPT, run in a workspace:
id
node --version
python3 --version
uv --version
docker version
docker compose version
apt-get updateThen validate nested services:
docker run -d --name smoke-postgres \
-e POSTGRES_PASSWORD=postgres \
-p 5432:5432 \
postgres:16
docker psPersistence
For workspace <id>:
$HOST_DATA_DIR/workspaces/<id>/repo -> /workspace
$HOST_DATA_DIR/workspaces/<id>/home -> /home/agent
$HOST_DATA_DIR/workspaces/<id>/docker -> /var/lib/dockerCloud credentials and CLI state survive recreation when stored under /home/agent, including:
/home/agent/.aws
/home/agent/.azure
/home/agent/.config/gcloud
/home/agent/.kube
/home/agent/.cache
/home/agent/.localGit push
Push remains a dedicated audited MCP tool. To enable it:
ENABLE_GIT_PUSH=true
GITHUB_TOKEN=<short-lived-token>Then recreate the MCP controller:
docker compose --env-file .env up -d --force-recreate mcpDo not put the GitHub token inside a workstation. The controller injects it only into the host-side push process.
Security boundary
Workstation mode is intentionally powerful. The container is privileged because nested Docker requires it. The security boundary is the workstation container plus its dedicated mounted directories—not command-level restrictions inside the workstation.
It does not mount:
the host Docker socket;
arbitrary host directories;
the MCP controller's secrets;
the macOS filesystem.
Use this mode on a dedicated Docker Desktop context or, later, move the same image to a dedicated VM for stronger isolation.
Main tools
The existing MCP tools remain compatible. Version 0.2.0 adds workspace_recreate_runtime, which replaces a runtime while preserving its persistent state.
This server cannot be deployed
Maintenance
Related MCP Connectors
A persistent Linux computer for your AI: what it installs and writes survives the session.
Persistent Linux microVMs for agents: root, internet, sub-second resume and a public URL.
Zero-Ops deploy of a private AI workspace to your own VPS — from your AI chat. Free and open-source.
Develop, manage, and debug Railway projects, services, and deployments from within agents.
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