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Codex Delegate MCP Server

Developer ToolsUse Caution4.2MCP RegistryLocal
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Server data from the Official MCP Registry

Bridge AI coding hosts to the OpenAI Codex CLI for delegated implementation.

About

Bridge AI coding hosts to the OpenAI Codex CLI for delegated implementation.

Security Report

4.2
Use Caution4.2High Risk

Codex Delegate MCP is a well-structured tool for delegating code implementation tasks to OpenAI's Codex CLI. The codebase demonstrates solid engineering practices with comprehensive test coverage, proper error handling, and reasonable permission scoping. No authentication vulnerabilities, credential leaks, or malicious patterns were detected. Minor code quality observations exist but do not materially impact security. Supply chain analysis found 3 known vulnerabilities in dependencies (0 critical, 3 high severity). Package verification found 1 issue.

4 files analyzed · 8 issues found

Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.

Permissions Required

This plugin requests these system permissions. Most are normal for its category.

File System Read

Reads files on your machine. Normal for tools that analyze or process local data.

File System Write

Writes or modifies files on your machine. Check that this is expected for the tool.

file_delete

Check that this permission is expected for this type of plugin.

process_spawn

Check that this permission is expected for this type of plugin.

env_vars

Check that this permission is expected for this type of plugin.

HTTP Network Access

Connects to external APIs or services over the internet.

How to Install

Add this to your MCP configuration file:

{
  "mcpServers": {
    "io-github-andreilungeanu-codex-delegate-mcp": {
      "args": [
        "-y",
        "codex-delegate-mcp"
      ],
      "command": "npx"
    }
  }
}

Documentation

View on GitHub

From the project's GitHub README.

Codex Delegate MCP

Stop burning your frontier agent's limits on boilerplate.

Delegate implementation to the OpenAI Codex CLI — your agent writes the brief and reviews the diff.

npm version npm downloads MCP Registry codex-delegate-mcp MCP server node license: MIT tests

Use your best coding agent where its judgment matters most: understanding the task, shaping the plan, and reviewing the result.

Codex Delegate is the MCP bridge that lets Claude Code, Cursor, Copilot — or any MCP client — hand implementation to the OpenAI Codex CLI, then get a clean, structured result back for review.

🧠 Frontier quality, kept

Your assistant does what frontier models are actually for: understands the task, writes a precise brief, reviews the finished diff. Codex holds its own as the implementer — guided and checked by a smarter orchestrator. The result reads like frontier work, because a frontier model planned it and signed off on it.

⚡ Done faster

Codex tears through multi-file edits while a frontier chat model would still be streaming the first file. You delegate, keep working with your assistant, and the diff shows up done.

🔋 Your limits stop being the bottleneck

Delegated work runs on the OpenAI Codex CLI and its own usage — separate from your orchestrator's chat quota. Your Claude, Cursor, or Copilot subscription spends tokens on the brief and the review; Codex does the grinding. On API? That's the per-token grind moved off your main bill.

You and your agent understand the task, write the brief and review the diff; the MCP delegate tool hands that brief to the OpenAI Codex CLI, which implements it and edits your workspace; one compact JSON result comes back with what changed, which files, and the thread id

A delegate result: one compact JSON block with the final answer, status, thread and delegation ids, workspace, Codex CLI version, per-turn token usage, and the files the edit tools reported changing

Features

  • 🤝 Native plugins — install into Claude Code, Cursor, or GitHub Copilot CLI and just say "delegate this to Codex". The shared skill teaches your agent how to delegate well.
  • 📦 Clean, typed results — one compact JSON block: the final answer, status, the files Codex edited, and per-turn token counts. Fields that carry no signal are omitted, so anything present is worth reading.
  • 📋 Four modesagent edits, plan returns a schema-validated plan you approve before anything is written, ask is read-only Q&A, and review runs Codex's own reviewer over uncommitted work, a base branch, or a single commit.
  • 🧵 Resume — continue the same Codex thread with resumeThreadId, and get told if the context didn't actually carry over.
  • 🧑‍🤝‍🧑 Parallel, and cancellable for real — fan a question across models or put independent workers on independent directories; cancel returns once the process has ended, not once the kill was requested.
  • 🩺 Self-diagnosing — a doctor tool that tells you exactly what's missing if setup isn't right.
  • 🔌 Works everywhere MCP does — VS Code, JetBrains, Windsurf, Visual Studio, and more.

The caveats are documented rather than buried: what an empty warnings does not prove, and when result is salvage instead of an answer, are in the delegate reference.

Install

You need Node.js 20+ and the OpenAI Codex CLI, already logged in (codex login).

Claude Code

/plugin marketplace add andreilungeanu/codex-delegate-mcp
/plugin install codex-delegate-mcp@codex-delegate-mcp

Then just ask:

Delegate to Codex: migrate src/api from callbacks to async/await and update the tests, then walk me through what changed.

That's the whole loop — Claude writes the brief, Codex grinds through the files, Claude walks you through the diff.

Cursor

Add an MCP server in Cursor Settings → MCP (or project .cursor/mcp.json):

{
  "mcpServers": {
    "codex-delegate-mcp": {
      "command": "npx",
      "args": ["-y", "codex-delegate-mcp"]
    }
  }
}

Then ask Cursor to delegate implementation to Codex the same way.

GitHub Copilot CLI

copilot plugin install andreilungeanu/codex-delegate-mcp

More clients

Install in VS Code Install in VS Code Insiders

{
  "servers": {
    "codex-delegate-mcp": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "codex-delegate-mcp"]
    }
  }
}

Or run Chat: Install Plugin From Source with this repository's URL.

Under Settings → Tools → AI Assistant → Model Context Protocol (MCP), add a server with command npx and arguments -y codex-delegate-mcp.

{
  "mcpServers": {
    "codex-delegate-mcp": {
      "command": "npx",
      "args": ["-y", "codex-delegate-mcp"]
    }
  }
}

Heads-up: Cascade caps you at 100 tools across all servers.

{
  "servers": {
    "codex-delegate-mcp": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "codex-delegate-mcp"]
    }
  }
}

Requires 17.14+. Note the top-level key is servers, not mcpServers.

Kiro, Kilo Code, and any other MCP client

Add the following server to the client's MCP config:

{
  "mcpServers": {
    "codex-delegate-mcp": {
      "command": "npx",
      "args": ["-y", "codex-delegate-mcp"]
    }
  }
}

MIT © Andrei Lungeanu

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