Sandbox Mode

Gemini CLI ships a sandboxed code-execution environment that lets the model write and run code in an isolated context. This is a Gemini CLI feature, not a feature of the MCP server.

Why isn't there a sandbox parameter on ask-gemini anymore?

ADR-034 simplified the ask-gemini MCP tool schema from 8 parameters to 2 (prompt + model) for token efficiency and to reduce LLM-induced parameter hallucinations. The sandbox parameter was one of the casualties — it's a niche feature that most users don't need, and exposing it added noise to every Claude/Codex/Cursor instance loading the tool definition.

The underlying executor still supports sandbox mode programmatically — only the MCP-facing schema dropped it.

How to use sandbox mode today

If you need Gemini's sandbox, run gemini directly from your terminal with the -s flag:

gemini -s -p "Write a Python script that sorts a list and run it"

Inside Claude Code, you can dispatch this via Bash:

Run this in bash: gemini -s -p "Write and execute a Python script that validates this JSON: ..."

The plugin's ask-gemini-run binary (a small node wrapper) also passes through to the executor — you can adapt it if you want a programmatic path.

When you'd actually want sandbox mode

• Testing snippets the model just generated (write + execute in one round-trip)
• Quick proof-of-concepts where you want runtime evidence, not just code
• Learning — see code execute with real output

For most workflows (review, analysis, refactor suggestions), sandbox is unnecessary and the simpler ask-gemini / ask-llm MCP tools are the right call.

Limitations

Sandbox capabilities depend on your Gemini CLI version and Gemini account. See the Gemini CLI documentation for current sandbox features and constraints.