Codex Gemini Delegator V2

A robust, production-ready MCP (Model Context Protocol) server that allows OpenAI Codex to supervise and delegate tasks to Google Gemini (Antigravity) workers as subordinate agents.

Unlike other bridges, this delegator treats Gemini workers as resilient background jobs. It orchestrates isolated Git worktrees, enforces strict security boundaries, monitors stream-json for infinite loop failures, and auto-nudges stuck workers to unblock them.

Key Features

1. True Git Worktree Isolation: When Codex delegates a task, the delegator automatically spawns an invisible Git worktree (.worktrees/wt-<uuid>). Gemini executes its code changes strictly inside this isolated environment. Your main branch remains completely untouched until Codex explicitly applies the run.

2. First-Party API Alignment: This MCP server exposes the exact tool names and signatures expected by mainstream Codex delegators (delegate_to_agent, apply_agent_run, get_agent_run_report, etc.).

3. Loop Detection & Auto-Nudging: Built-in state heuristics actively monitor the stream-json output of the Gemini worker. If the worker gets stuck in an infinite tool failure loop or tries the exact same broken command 3 times in a row, the Supervisor forcefully restarts it with a recursive --session-id and a strict system nudge to change strategies.

4. Symlink-Resistant Security Boundaries: Subordinate workers are hardened against path traversal and symlink vulnerabilities. A custom hook (enforce_boundaries.py) prevents them from executing destructive commands (rm -rf, git reset) and strictly jails their write access to their delegated scope.

5. SQLite WAL Persistence: All runs, PIDs, and logs are tracked in a lightning-fast SQLite WAL ledger. If you close your Codex session, the Gemini workers keep running in the background and their state is fully recoverable.

Related MCP server: unlimited-mcp

Prerequisites

• Google Antigravity (gemini CLI) installed globally.

• Python 3.10+

• Codex CLI (codex)

Installation & Bootstrapping

1. Clone the repository:

   git clone https://github.com/psychofanplays/gemini4codex-mcp.git
   cd gemini4codex

2. Register the MCP Server in Codex using uv: Add the following to your ~/.codex/config.toml (or equivalent Codex MCP configuration). We highly recommend using uv to automatically manage the environment and dependencies:

   [mcp.servers.gemini-delegator]
   command = "uv"
   args = [
       "--directory", 
       "/ABSOLUTE/PATH/TO/gemini4codex", 
       "run", 
       "-m",
       "server.gemini_delegator"
   ]

3. Provide Codex with the Bootstrapping Instructions: Once connected, you must instruct Codex to read the BOOTSTRAP.md file located in this repository. This file provides Codex with the explicit instructions on how to structure the Multi-Agent Hierarchy and how to leverage gemini-3.1-pro and gemini-3.6-flash as subordinate agents.

   Example Prompt for Codex:

   "I have just connected the gemini-delegator MCP server. Please read the BOOTSTRAP.md file in the gemini4codex repository and apply the agent synergy patterns to your global memory."

How It Works

When Codex is connected to the MCP server, it gains access to the following tools:

• list_agent_backends: Verifies the Gemini CLI and DB are healthy.

• list_agent_runs: Displays all active, idle, and failed background workers.

• delegate_to_agent: Spawns a new Gemini worker inside a new UUID Git Worktree.

• continue_agent_run: Sends a follow-up instruction to an existing worker.

• get_agent_run_report: Returns the worker's JSON logs, execution status, and importantly, the raw Git diff of what the worker changed inside its worktree.

• apply_agent_run: Performs a squash merge of the worker's temporary worktree into your main branch.

• cleanup_agent_run: Cancels a running worker and deletes its isolated worktree.

Example Workflow (From Codex's Perspective)

1. Codex: "I need to refactor the database schema, but I don't want to break the app. I'll delegate this to a Gemini worker."

2. Codex calls delegate_to_agent(worker_id="db-refactor", workspace_path=".")

3. Delegator Server creates .worktrees/wt-5f8a9b2c and runs the google.antigravity SDK in-process inside it.

4. Gemini works in the background, modifying files. If it loops or gets stuck, the Supervisor auto-nudges it.

5. Codex periodically calls get_agent_run_report("db-refactor").

6. Codex reads the git diff returned by the report. "Looks good, the tests passed."

7. Codex calls apply_agent_run("db-refactor").

8. Delegator Server squash merges the changes cleanly into the main branch but explicitly leaves them staged (no auto-commit), allowing Codex or the human user to review and finalize the commit.

Security

This plugin aggressively restricts the Gemini subordinate worker:

• True OS Sandboxing: The Delegator explicitly prevents subordinate workers from bypassing the Antigravity OS sandbox, meaning they are natively isolated from the filesystem at the kernel level and cannot modify files outside the delegated scope.

• Git Sandboxing: Workers are forbidden from running structural git commands (git commit, git push, git merge) or destructive operations (rm -rf).

• Profile Segregation: You can delegate a scout or reviewer profile, which disables all write tools completely.

Architecture Map

The project is structured into three main layers:

gemini4codex/
├── pyproject.toml           # Python packaging and dependency config
├── BOOTSTRAP.md             # Essential instructions for Codex on how to use these agents
└── server/
    ├── gemini_delegator.py  # The FastMCP Server exposing endpoints to Codex
    ├── supervisor.py        # Async execution engine; parses stream-json & detects loops
    ├── worktree.py          # Git worktree isolation and squash-merge orchestrator
    ├── security.py          # Dynamic SDK hooks to jail the worker
    └── ledger.py            # SQLite WAL state manager for robust persistence

• Layer 1: The Codex Interface (gemini_delegator.py) handles all incoming MCP requests.

• Layer 2: The Orchestrator (worktree.py & supervisor.py) spins up the isolated environment and runs the process asynchronously via the Antigravity SDK.

• Layer 3: The Jailed Subordinate (security.py) restricts the worker's context natively so it cannot harm the host system or primary branch.