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Gemini CLI Configuration

The Gemini CLI offers several ways to configure its behavior, from environment variables and command-line arguments to dedicated settings files. This document outlines the different configuration methods and available settings.

Configuration Layers

Configuration is typically applied in the following order of precedence (lower numbers are overridden by higher numbers):

Default Values: Hardcoded defaults within the application.
User Settings File: Global settings for the current user.
Project Settings File: Project-specific settings.
Environment Variables: System-wide or session-specific variables, potentially loaded from .env files.
Command-line Arguments: Values passed when launching the CLI.

1. Settings Files (`settings.json`)

The Gemini CLI uses settings.json files for persistent configuration. There are two main locations for these files:

User Settings:
- Location: ~/.gemini/settings.json (where ~ is your home directory).
- Scope: Applies globally to all Gemini CLI sessions for the current user.
Project Settings:
- Location: .gemini/settings.json within your project's root directory.
- Scope: Applies only when running Gemini CLI from that specific project. Project settings override User settings.

Note on Environment Variables in Settings: String values within your settings.json files can reference environment variables using either $VAR_NAME or ${VAR_NAME} syntax. These variables will be automatically resolved when the settings are loaded. For example, if you have an environment variable MY_API_TOKEN, you could use it in settings.json like this: "apiKey": "$MY_API_TOKEN".

The `.gemini` Directory in Your Project

When you create a .gemini/settings.json file for project-specific settings, or when the system needs to store project-specific information, this .gemini directory is used.

Purpose:

Stores project-specific configuration for the Gemini CLI (in settings.json).
Can hold other project-specific files related to Gemini CLI's operation, such as:
- Custom sandbox profiles (e.g., .gemini/sandbox-macos-custom.sb, .gemini/sandbox.Dockerfile).
- A project-specific core system prompt override file (e.g., .gemini/system.md). If present, this file can be used to override the default system prompt for the project.

Available Settings in `settings.json`:

contextFileName (string, optional):
- Description: Specifies the filename for context files (e.g., GEMINI.md, AGENTS.md).
- Default: GEMINI.md
- Example: "contextFileName": "AGENTS.md"
fileFiltering (object, optional):
- Description: Controls git-aware file filtering behavior for @ commands and file discovery tools.
- Properties:
  - respectGitIgnore (boolean, default: true): Whether to respect .gitignore patterns when discovering files. When enabled, git-ignored files (like node_modules/, dist/, .env) are automatically excluded from @ commands and file listing operations.
  - customIgnorePatterns (array of strings, default: []): Additional patterns to ignore beyond git-ignored files. Useful for excluding specific directories or file types.
  - allowBuildArtifacts (boolean, default: false): Whether to include build artifacts and generated files in file discovery operations.
- Example:
```
"fileFiltering": {
  "respectGitIgnore": true,
  "customIgnorePatterns": ["temp/", "*.log"],
  "allowBuildArtifacts": false
}
```
coreTools (array of strings, optional):
- Description: Allows you to specify a list of core tool names that should be made available to the model. This can be used to restrict or customize the set of built-in tools.
- Example: "coreTools": ["ReadFileTool", "GlobTool", "SearchText"].
- Behavior: If this setting is provided, only the listed tools will be available for the model to use. If omitted, all default core tools are available. See Built-in Tools for a list of core tools. You can also specify the alternative internal tool names used by the model, e.g. read_file, and you can get a full listing for that by simply asking the model "what tools do you have?".
autoAccept (boolean, optional):
- Description: Controls whether the CLI automatically accepts and executes tool calls that are considered safe (e.g., read-only operations) without explicit user confirmation.
- Default: false (users will be prompted for most tool calls).
- Behavior:
  - If set to true, the CLI will bypass the confirmation prompt for tools deemed safe. An indicator may be shown in the UI when auto-accept is active.
  - Potentially destructive or system-modifying tools (like run_shell_command or write_file) will likely still require confirmation regardless of this setting.
- Example: "autoAccept": true
theme (string):
- Specifies the visual theme for the CLI.
- Example: "theme": "VS2015"
- See the Theming section in README.md for available theme names.
sandbox (boolean or string):
- Controls whether and how to use sandboxing for tool execution.
- If a .gemini/sandbox.Dockerfile exists in your project, it will be used to build a custom sandbox image.
- true: Enable default sandbox (see README for behavior).
- false: Disable sandboxing (WARNING: this is inherently unsafe).
- "docker" or "podman": Explicitly choose container-based sandboxing command.
- <command>: Specify custom command for container-based sandboxing.

toolDiscoveryCommand (string, advanced):

Custom shell command for discovering tools from your project, if available.

Must return on stdout a JSON array of function declarations.

Tool wrappers, i.e. [{ "function_declarations": [...] }, ...], are optional.

Example for a single function add_two_numbers(a, b):

[
  {
    "name": "add_two_numbers",
    "description": "Add two numbers.",
    "parameters": {
      "type": "object",
      "properties": {
        "a": {
          "type": "integer",
          "description": "first number"
        },
        "b": {
          "type": "integer",
          "description": "second number"
        }
      },
      "required": [
        "a",
        "b"
      ]
    }
  }
]

toolCallCommand (string, advanced):
- Custom shell command for calling a specific tool discovered via toolDiscoveryCommand.
- Must take function name (exactly as in function declaration) as first command line argument.
- Must read function arguments as JSON on stdin, analogous to functionCall.args.
  - Example for add_two_numbers (see above): {"a":1, "b":2}
- Must return function output as JSON on stdout, analogous to functionResponse.response.content.
  - Example for add_two_numbers (see above): 3 (for input {"a":1, "b":2} on stdin)
mcpServers (object, advanced):
- Configures connections to one or more Model-Context Protocol (MCP) servers for discovering and using custom tools.
- This is an object where each key is a unique server name (alias) and the value is an object defining that server's parameters:
  - command (string, required): The command to execute to start the MCP server.
  - args (array of strings, optional): Arguments to pass to the command.
  - env (object, optional): Environment variables to set for the server process.
  - cwd (string, optional): The working directory in which to start the server.
  - timeout (number, optional): Timeout in milliseconds for requests to this MCP server.
  - trust (boolean, optional): Trust this server and bypass all tool call confirmations.
- Behavior:
  - The CLI will attempt to connect to each configured MCP server to discover available tools.
  - If multiple MCP servers expose a tool with the same name, the tool names will be prefixed with the server alias you defined in the configuration (e.g., serverAlias__actualToolName) to avoid conflicts.
  - The system may strip certain schema properties from MCP tool definitions for compatibility.
- Example:
```
"mcpServers": {
  "myPythonServer": {
    "command": "python",
    "args": ["mcp_server.py", "--port", "8080"],
    "cwd": "./mcp_tools/python",
    "timeout": 5000
  },
  "myNodeServer": {
    "command": "node",
    "args": ["mcp_server.js"],
    "cwd": "./mcp_tools/node"
  },
  "myDockerServer": {
    "command": "docker",
    "args": ["run", "i", "--rm", "-e", "API_KEY", "ghcr.io/foo/bar"],
    "env": {
      "API_KEY": "$MY_API_TOKEN"
    }
  },
}
```
- mcpServerCommand (string, advanced, deprecated):
  - Legacy setting for configuring a single MCP server. Please use mcpServers instead for better flexibility and support for multiple servers.

Example `settings.json`:

{
  "theme": "VS2015",
  "sandbox": "docker",
  "toolDiscoveryCommand": "bin/get_tools",
  "toolCallCommand": "bin/call_tool",
  "mcpServers": {
    "mainServer": {
      "command": "bin/mcp_server.py"
    },
    "anotherServer": {
      "command": "node",
      "args": ["mcp_server.js", "--verbose"]
    }
  }
}

2. Environment Variables & `.env` Files

Environment variables are a common way to configure applications, especially for sensitive information like API keys or for settings that might change between environments.

The CLI automatically loads environment variables from an .env file. The loading order is:

.env file in the current working directory.
If not found, it searches upwards in parent directories until it finds an .env file or reaches the project root (identified by a .git folder) or the home directory.
If still not found, it looks for ~/.env (in the user's home directory).

GEMINI_API_KEY (Required):
- Your API key for the Gemini API.
- Crucial for operation. The CLI will not function without it.
- Set this in your shell profile (e.g., ~/.bashrc, ~/.zshrc) or an .env file.
GEMINI_MODEL:
- Specifies the default Gemini model to use.
- Overrides the hardcoded default, which is currently gemini-2.5-pro-preview-05-06.
- Example: export GEMINI_MODEL="gemini-1.5-flash-latest"
GEMINI_SANDBOX:
- Alternative to the sandbox setting in settings.json.
- Accepts true, false, docker, podman, or a custom command string.
SEATBELT_PROFILE (macOS specific):
- Switches the Seatbelt (sandbox-exec) profile on macOS.
- minimal: (Default) Restricts writes to the project folder (and a few other folders, see packages/cli/src/utils/sandbox-macos-minimal.sb) but allows other operations.
- strict: Uses a strict profile that declines operations by default.
- <profile_name>: Uses a custom profile. To define a custom profile, create a file named sandbox-macos-<profile_name>.sb in your project's .gemini/ directory (e.g., my-project/.gemini/sandbox-macos-custom.sb).
DEBUG or DEBUG_MODE (often used by underlying libraries or the CLI itself):
- Set to true or 1 to enable verbose debug logging, which can be helpful for troubleshooting.
NO_COLOR:
- Set to any value to disable all color output in the CLI.
CLI_TITLE:
- Set to a string to customize the title of the CLI.

3. Command-Line Arguments

Arguments passed directly when running the CLI can override other configurations for that specific session.

--model <model_name> (or -m <model_name>):
- Specifies the Gemini model to use for this session.
- Example: npm start -- --model gemini-1.5-pro-latest
--sandbox (or -s):
- Enables sandbox mode for this session. The exact behavior might depend on other sandbox configurations (environment variables, settings files).
--debug_mode (or -d):
- Enables debug mode for this session, providing more verbose output.
--question <your_question> (or -q <your_question>):
- Used to pass a question directly to the command, especially when piping input to the CLI.
--all_files (or -a):
- If set, recursively includes all files within the current directory as context for the prompt.
--help (or -h):
- Displays help information about command-line arguments.

4. Context Files (Hierarchical Instructional Context)

While not strictly configuration for the CLI's behavior, context files (defaulting to GEMINI.md but configurable via the contextFileName setting) are crucial for configuring the instructional context (also referred to as "memory") provided to the Gemini model. This powerful feature allows you to give project-specific instructions, coding style guides, or any relevant background information to the AI, making its responses more tailored and accurate to your needs. The CLI includes UI elements, such as an indicator in the footer showing the number of loaded context files, to keep you informed about the active context.

Purpose: These Markdown files contain instructions, guidelines, or context that you want the Gemini model to be aware of during your interactions. The system is designed to manage this instructional context hierarchically.

Example Context File Content (e.g., `GEMINI.md`)

Here's a conceptual example of what a context file at the root of a TypeScript project might contain:

# Project: My Awesome TypeScript Library

## General Instructions:

- When generating new TypeScript code, please follow the existing coding style.
- Ensure all new functions and classes have JSDoc comments.
- Prefer functional programming paradigms where appropriate.
- All code should be compatible with TypeScript 5.0 and Node.js 18+.

## Coding Style:

- Use 2 spaces for indentation.
- Interface names should be prefixed with `I` (e.g., `IUserService`).
- Private class members should be prefixed with an underscore (`_`).
- Always use strict equality (`===` and `!==`).

## Specific Component: `src/api/client.ts`

- This file handles all outbound API requests.
- When adding new API call functions, ensure they include robust error handling and logging.
- Use the existing `fetchWithRetry` utility for all GET requests.

## Regarding Dependencies:

- Avoid introducing new external dependencies unless absolutely necessary.
- If a new dependency is required, please state the reason.

This example demonstrates how you can provide general project context, specific coding conventions, and even notes about particular files or components. The more relevant and precise your context files are, the better the AI can assist you. Project-specific context files are highly encouraged to establish conventions and context.

Hierarchical Loading and Precedence: The CLI implements a sophisticated hierarchical memory system by loading context files (e.g., GEMINI.md) from several locations. Content from files lower in this list (more specific) typically overrides or supplements content from files higher up (more general). The exact concatenation order and final context can be inspected using the /showmemory command. The typical loading order is:
1. Global Context File:
  - Location: ~/.gemini/<contextFileName> (e.g., ~/.gemini/GEMINI.md in your user home directory).
  - Scope: Provides default instructions for all your projects.
2. Project Root & Ancestors Context Files:
  - Location: The CLI searches for the configured context file in the current working directory and then in each parent directory up to either the project root (identified by a .git folder) or your home directory.
  - Scope: Provides context relevant to the entire project or a significant portion of it.
3. Sub-directory Context Files (Contextual/Local):
  - Location: The CLI also scans for the configured context file in subdirectories below the current working directory (respecting common ignore patterns like node_modules, .git, etc.).
  - Scope: Allows for highly specific instructions relevant to a particular component, module, or sub-section of your project.
Concatenation & UI Indication: The contents of all found context files are concatenated (with separators indicating their origin and path) and provided as part of the system prompt to the Gemini model. The CLI footer displays the count of loaded context files, giving you a quick visual cue about the active instructional context.
Commands for Memory Management:
- Use /memory refresh to force a re-scan and reload of all context files from all configured locations. This updates the AI's instructional context.
- Use /memory show to display the combined instructional context currently loaded, allowing you to verify the hierarchy and content being used by the AI.
- See the Commands documentation for full details on the /memory command and its sub-commands (show and refresh).

By understanding and utilizing these configuration layers and the hierarchical nature of context files, you can effectively manage the AI's memory and tailor the Gemini CLI's responses to your specific needs and projects.

Sandboxing

The Gemini CLI can execute potentially unsafe operations (like shell commands and file modifications) within a sandboxed environment to protect your system.

Sandboxing is disabled by default, but you can enable it in a few ways:

Using --sandbox or -s flag.
Setting GEMINI_SANDBOX environment variable.
Sandbox is enabled in --yolo mode by default.

By default, it uses a pre-built gemini-cli-sandbox Docker image.

For project-specific sandboxing needs, you can create a custom Dockerfile at .gemini/sandbox.Dockerfile in your project's root directory. This Dockerfile can be based on the base sandbox image:

FROM gemini-cli-sandbox

# Add your custom dependencies or configurations here
# For example:
# RUN apt-get update && apt-get install -y some-package
# COPY ./my-config /app/my-config

When .gemini/sandbox.Dockerfile exists, you can use BUILD_SANDBOX environment variable when running Gemini CLI to automatically build the custom sandbox image:

BUILD_SANDBOX=1 gemini -s

Theming

The Gemini CLI supports theming to customize its color scheme and appearance. Themes define colors for text, backgrounds, syntax highlighting, and other UI elements.

Available Themes

The CLI comes with a selection of pre-defined themes. As seen in theme-manager.ts, these typically include:

Dark Themes:
- AtomOneDark
- Dracula
- VS2015 (Default)
- GitHub (Dark variant usually)
Light Themes:
- VS (Visual Studio Light)
- GoogleCode
- XCode (Light variant usually)
ANSI:
- ANSI: A theme that primarily uses the terminal's native ANSI color capabilities.

(The exact list and their appearance can be confirmed by running the /theme command within the CLI.)

Changing Themes

Type the /theme command in the CLI.
A dialog or selection prompt (ThemeDialog.tsx) will appear, listing the available themes.
You can typically navigate (e.g., with arrow keys) and select a theme. Some interfaces might offer a live preview or highlight as you select.
Confirm your selection (often with Enter) to apply the theme. You can usually cancel out of the selection (e.g., with Escape).

Theme Persistence

Selected themes are usually saved in the CLI's configuration (see CLI Configuration) so your preference is remembered across sessions.

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