Gemini CLI Configuration

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

Configuration layers

Configuration is 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.

The user settings file and project settings file

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

User settings file:
- Location: ~/.gemini/settings.json (where ~ is your home directory).
- Scope: Applies to all Gemini CLI sessions for the current user.
Project settings file:
- 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

In addition to a project settings file, a project's .gemini directory can contain 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).

Available settings in `settings.json`:

contextFileName (string or array of strings):
- Description: Specifies the filename for context files (e.g., GEMINI.md, AGENTS.md). Can be a single filename or a list of accepted filenames.
- Default: GEMINI.md
- Example: "contextFileName": "AGENTS.md"
bugCommand (object):
- Description: Overrides the default URL for the /bug command.
- Default: "urlTemplate": "https://github.com/google-gemini/gemini-cli/issues/new?template=bug_report.yml&title={title}&info={info}"
- Properties:
  - urlTemplate (string): A URL that can contain {title} and {info} placeholders.
- Example:
  json
```
"bugCommand": {
  "urlTemplate": "https://bug.example.com/new?title={title}&info={info}"
}
```
  1
  2
  3
fileFiltering (object):
- Description: Controls git-aware file filtering behavior for @ commands and file discovery tools.
- Default: "respectGitIgnore": true, "enableRecursiveFileSearch": true
- Properties:
  - respectGitIgnore (boolean): Whether to respect .gitignore patterns when discovering files. When set to true, git-ignored files (like node_modules/, dist/, .env) are automatically excluded from @ commands and file listing operations.
  - enableRecursiveFileSearch (boolean): Whether to enable searching recursively for filenames under the current tree when completing @ prefixes in the prompt.
- Example:
  json
```
"fileFiltering": {
  "respectGitIgnore": true,
  "enableRecursiveFileSearch": false
}
```
  1
  2
  3
  4
coreTools (array of strings):
- 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 the set of built-in tools. See Built-in Tools for a list of core tools.
- Default: All tools available for use by the Gemini model.
- Example: "coreTools": ["ReadFileTool", "GlobTool", "SearchText"].
excludeTools (array of strings):
- Description: Allows you to specify a list of core tool names that should be excluded from the model. A tool listed in both excludeTools and coreTools is excluded.
- Default: No tools excluded.
- Example: "excludeTools": ["run_shell_command", "findFiles"].
autoAccept (boolean):
- Description: Controls whether the CLI automatically accepts and executes tool calls that are considered safe (e.g., read-only operations) without explicit user confirmation. If set to true, the CLI will bypass the confirmation prompt for tools deemed safe.
- Default: false
- Example: "autoAccept": true
theme (string):
- Description: Sets the visual theme for Gemini CLI.
- Default: "Default"
- Example: "theme": "GitHub"
sandbox (boolean or string):
- Description: Controls whether and how to use sandboxing for tool execution. If set to true, Gemini CLI uses a pre-built gemini-cli-sandbox Docker image. For more information, see Sandboxing.
- Default: false
- Example: "sandbox": "docker"
toolDiscoveryCommand (string):
- Description: Defines a custom shell command for discovering tools from your project. The shell command must return on stdout a JSON array of function declarations. Tool wrappers are optional.
- Default: Empty
- Example: "toolDiscoveryCommand": "bin/get_tools"
toolCallCommand (string):
- Description: Defines a custom shell command for calling a specific tool that was discovered using toolDiscoveryCommand. The shell command must meet the following criteria:
  - It must take function name (exactly as in function declaration) as first command line argument.
  - It must read function arguments as JSON on stdin, analogous to functionCall.args.
  - It must return function output as JSON on stdout, analogous to functionResponse.response.content.
- Default: Empty
- Example: "toolCallCommand": "bin/call_tool"
mcpServers (object):
- Description: Configures connections to one or more Model-Context Protocol (MCP) servers for discovering and using custom tools. Gemini CLI attempts 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. Note that the system might strip certain schema properties from MCP tool definitions for compatibility.
- Default: Empty
- Properties:
  - <SERVER_NAME> (object): The server parameters for the named server.
    - 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.
- Example:
  json
```
"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"
    }
  },
}
```
  1
  2
  3
  4
  5
  6
  7
  8
  9
  10
  11
  12
  13
  14
  15
  16
  17
  18
  19
  20
checkpointing (object):
- Description: Configures the checkpointing feature, which allows you to save and restore conversation and file states. See the Checkpointing documentation for more details.
- Default: {"enabled": false}
- Properties:
  - enabled (boolean): When true, the /restore command is available.
preferredEditor (string):
- Description: Specifies the preferred editor to use for viewing diffs.
- Default: vscode
- Example: "preferredEditor": "vscode"
telemetry (object)
- Description: Configures logging and metrics collection for Gemini CLI. For more information, see Telemetry.
- Default: {"enabled": false, "target": "local", "otlpEndpoint": "http://localhost:4317", "logPrompts": true}
- Properties:
  - enabled (boolean): Whether or not telemetry is enabled.
  - target (string): The destination for collected telemetry. Supported values are local and gcp.
  - otlpEndpoint (string): The endpoint for the OTLP Exporter.
  - logPrompts (boolean): Whether or not to include the content of user prompts in the logs.
- Example:
  json
```
"telemetry": {
  "enabled": true,
  "target": "local",
  "otlpEndpoint": "http://localhost:16686",
  "logPrompts": false
}
```
  1
  2
  3
  4
  5
  6
usageStatisticsEnabled (boolean):
- Description: Enables or disables the collection of usage statistics. See Usage Statistics for more information.
- Default: true
- Example:
  json
```
"usageStatisticsEnabled": false
```
  1

Example `settings.json`:

json

{
  "theme": "GitHub",
  "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"]
    }
  },
  "telemetry": {
    "enabled": true,
    "target": "local",
    "otlpEndpoint": "http://localhost:4317",
    "logPrompts": true
  },
  "usageStatisticsEnabled": true
}

Shell History

The CLI keeps a history of shell commands you run. To avoid conflicts between different projects, this history is stored in a project-specific directory within your user's home folder.

Location: ~/.gemini/tmp/<project_hash>/shell_history
- <project_hash> is a unique identifier generated from your project's root path.
- The history is stored in a file named shell_history.

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
- Example: export GEMINI_MODEL="gemini-2.5-flash"
GOOGLE_API_KEY:
- Your Google Cloud API key.
- Required for using Vertex AI in express mode.
- Ensure you have the necessary permissions and set the GOOGLE_GENAI_USE_VERTEXAI=true environment variable.
- Example: export GOOGLE_API_KEY="YOUR_GOOGLE_API_KEY".
GOOGLE_CLOUD_PROJECT:
- Your Google Cloud Project ID.
- Required for using Code Assist or Vertex AI.
- If using Vertex AI, ensure you have the necessary permissions and set the GOOGLE_GENAI_USE_VERTEXAI=true environment variable.
- Example: export GOOGLE_CLOUD_PROJECT="YOUR_PROJECT_ID".
GOOGLE_APPLICATION_CREDENTIALS (string):
- Description: The path to your Google Application Credentials JSON file.
- Example: export GOOGLE_APPLICATION_CREDENTIALS="/path/to/your/credentials.json"
OTLP_GOOGLE_CLOUD_PROJECT:
- Your Google Cloud Project ID for Telemetry in Google Cloud
- Example: export OTLP_GOOGLE_CLOUD_PROJECT="YOUR_PROJECT_ID".
GOOGLE_CLOUD_LOCATION:
- Your Google Cloud Project Location (e.g., us-central1).
- Required for using Vertex AI in non express mode.
- If using Vertex AI, ensure you have the necessary permissions and set the GOOGLE_GENAI_USE_VERTEXAI=true environment variable.
- Example: export GOOGLE_CLOUD_LOCATION="YOUR_PROJECT_LOCATION".
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.
- permissive-open: (Default) Restricts writes to the project folder (and a few other folders, see packages/cli/src/utils/sandbox-macos-permissive-open.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.
CODE_ASSIST_ENDPOINT:
- Specifies the endpoint for the code assist server.
- This is useful for development and testing.

Command-Line Arguments

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

--model <model_name> (-m <model_name>):
- Specifies the Gemini model to use for this session.
- Example: npm start -- --model gemini-1.5-pro-latest
--prompt <your_prompt> (-p <your_prompt>):
- Used to pass a prompt directly to the command. This invokes Gemini CLI in a non-interactive mode.
--sandbox (-s):
- Enables sandbox mode for this session.
--sandbox-image:
- Sets the sandbox image URI.
--debug_mode (-d):
- Enables debug mode for this session, providing more verbose output.
--all_files (-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.
--show_memory_usage:
- Displays the current memory usage.
--yolo:
- Enables YOLO mode, which automatically approves all tool calls.
--telemetry:
- Enables telemetry.
--telemetry-target:
- Sets the telemetry target. See telemetry for more information.
--telemetry-otlp-endpoint:
- Sets the OTLP endpoint for telemetry. See telemetry for more information.
--telemetry-log-prompts:
- Enables logging of prompts for telemetry. See telemetry for more information.
--checkpointing:
- Enables checkpointing.
--version:
- Displays the version of the CLI.

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:

markdown

# 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 /memory show 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:

dockerfile

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:

bash

BUILD_SANDBOX=1 gemini -s

Usage Statistics

To help us improve the Gemini CLI, we collect anonymized usage statistics. This data helps us understand how the CLI is used, identify common issues, and prioritize new features.

What we collect:

Tool Calls: We log the names of the tools that are called, whether they succeed or fail, and how long they take to execute. We do not collect the arguments passed to the tools or any data returned by them.
API Requests: We log the Gemini model used for each request, the duration of the request, and whether it was successful. We do not collect the content of the prompts or responses.
Session Information: We collect information about the configuration of the CLI, such as the enabled tools and the approval mode.

What we DON'T collect:

Personally Identifiable Information (PII): We do not collect any personal information, such as your name, email address, or API keys.
Prompt and Response Content: We do not log the content of your prompts or the responses from the Gemini model.
File Content: We do not log the content of any files that are read or written by the CLI.

How to opt out:

You can opt out of usage statistics collection at any time by setting the usageStatisticsEnabled property to false in your settings.json file:

json

{
  "usageStatisticsEnabled": false
}

Gemini CLI Configuration ​

Configuration layers ​

The user settings file and project settings file ​

The .gemini directory in your project ​

Available settings in settings.json: ​

Example settings.json: ​

Shell History ​

Environment Variables & .env Files ​

Command-Line Arguments ​

Context Files (Hierarchical Instructional Context) ​

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

Sandboxing ​

Usage Statistics ​