AI CLI MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| AGY_CLI_PATH | No | Override path to the Antigravity CLI executable (agy.exe). If not set, auto-detected. | |
| CLI_YOLO_MODE | No | Runs commands with permission-bypass flags. Set to 'false' to disable YOLO mode. | true |
| CODEX_CLI_PATH | No | Override path to the codex executable (codex.exe). If not set, auto-detected. | |
| CLI_MAX_TIMEOUT | No | Maximum timeout ceiling in seconds (30 minutes). | 1800 |
| CLI_DEFAULT_TIMEOUT | No | Default timeout in seconds for CLI commands (5 minutes). | 300 |
| ALLOWED_WORKING_DIRECTORIES | No | Sandbox directory whitelist as a comma-separated list of allowed working directories. | * |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| codex_runA | Executes a coding prompt non-interactively using the OpenAI Codex CLI. Args: prompt: Detailed instruction or task description for the Codex agent. working_directory: Target project root directory where the task executes. model: Optional model override (e.g. o3-mini, o1, gpt-4o). timeout: Execution timeout in seconds (default: 300, max: 1800). yolo: When true, runs in YOLO mode (--dangerously-bypass-approvals-and-sandbox) for automated non-blocking execution. Returns: JSON string containing success status, exit code, execution time, stdout, and stderr. |
| antigravity_runA | Executes a coding prompt non-interactively using Google Antigravity CLI (agy). Args: prompt: Detailed instruction or task description for the Antigravity agent. working_directory: Target project root directory where the task executes. model: Optional model override (e.g. gemini-2.5-pro, gemini-2.5-flash). timeout: Execution timeout in seconds (default: 300, max: 1800). yolo: When true, runs in YOLO mode (--dangerously-skip-permissions) for automated non-blocking execution. Returns: JSON string containing success status, exit code, execution time, stdout, and stderr. |
| codex_reviewA | Performs an automated code review on a git repository using OpenAI Codex CLI. Args: working_directory: Root directory of the Git repository to review. instructions: Optional review focus areas or guidelines (e.g. security, memory leaks). model: Optional model override. timeout: Execution timeout in seconds (default: 300). uncommitted: When true, reviews uncommitted staged and unstaged changes. Returns: JSON string containing code review output, exit code, and execution summary. |
| antigravity_reviewB | Performs an automated code review on a workspace using Google Antigravity CLI. Args: working_directory: Root directory of the workspace or repository to review. instructions: Optional custom review criteria, guidelines, or focus areas. model: Optional model override. timeout: Execution timeout in seconds (default: 300). Returns: JSON string containing review critique, exit code, and execution summary. |
| cli_statusA | Checks the operational status of Codex CLI and Antigravity CLI binaries on the host. |
| get_agent_skillsA | Returns the comprehensive AI Agent Skills & Usage Guide for delegating tasks to Codex and Antigravity. Calling agents should read this guide to understand:
|
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| agent_orchestration_skills | MCP Prompt that primes an LLM with instructions on using the AI CLI gateway. |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
| read_skills_resource | MCP Resource providing the Agent Skills & Orchestration Guide. |
TDQS
Scored across 6 tools
The two run tools and two review tools are intentionally parallel but clearly distinguished by vendor (Codex vs. Antigravity), and cli_status/get_agent_skills are wholly distinct. The main confusion risk is between codex_run and antigravity_run, but descriptions make the target CLI explicit.
The core tools follow a consistent vendor_action pattern (codex_run, antigravity_run, codex_review, antigravity_review). cli_status and get_agent_skills break the pattern slightly, but they are also different kinds of operations and the names remain readable and predictable.
Six tools is a well-scoped set for a server that wraps two external CLI agents. Each tool covers a distinct operational need: execute, review, status check, and usage guidance.
The server covers the primary workflows one would expect: running and reviewing with both Codex and Antigravity, plus environment status and skill guidance. Minor gaps like model listing or installation tooling exist, but agents can work around them.