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Codex Delegate

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.

A terminal recording of Claude Code delegating to Codex: a health check confirms the Codex CLI, auth and model catalog; an ask-mode run diagnoses why the demo repo prints "today 0", naming commitDay() bucketing by UTC while cellDay() labels by local time, with line numbers; one sentence then fans out to two Codex models at once — one editing the repo, one researching in a separate directory — and the fix lands with tests passing and the footer reading today 4, current streak 23, longest streak 23; finally Codex reviews its own diff and reports three findings

🧠 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.

Related MCP server: Universal Coder Bridge

⚡ 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

  • 📦 One result you can review — a compact JSON block: the final answer, status, the files Codex's edit tools reported changing, per-turn token counts, and the threadId to continue from. Fields that carry no signal are omitted.

  • 📋 Plan first, then build it on the same threadplan returns schema-validated steps for you to approve, and agent implements them. ask answers questions. review runs Codex's own reviewer over uncommitted work, a base branch, or a single commit.

  • 🧵 Resume — continue a Codex thread with resumeThreadId. resumed: false tells you the context did not carry over.

  • 🧑‍🤝‍🧑 Run several, cancel cleanly — the same question across models, or independent workers on independent directories. cancel waits for the exit and warns when a process outlives the kill deadline.

  • 🤝 One-command install — Claude Code and GitHub Copilot CLI take it as a plugin, with a skill that teaches your agent how to delegate well. Cursor, VS Code, JetBrains, Windsurf and Visual Studio add the stdio server in settings.

  • 🩺 doctor — tells you exactly what's missing if setup isn't right.

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

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

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

MIT © Andrei Lungeanu

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