Codex Delegate

io.github.andreilungeanuPublished by GitHub account andreilungeanuv2.8.0Updated Nov 8, 2026

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

VerifiedSTDIODesktop onlyDeveloper ToolsAI & ML

Overview

AI-generated overview

Bridges an MCP client to the OpenAI Codex CLI so the assistant can delegate coding tasks, cancel runs, and diagnose setup.

What you can do
  • Delegate coding tasks to Codex with a spec, workspace and mode (agent, plan, ask, review), optionally resuming a thread or reviewing a diff, branch or commit
  • Cancel active runs by delegation ID, thread ID, or all at once, waiting for settlement
  • Diagnose plugin, CLI, login, recursion and workspace problems, with deeper quota and model-catalog checks
  • Return a compact JSON result with status, changed files, token counts and a thread ID to continue from
When to use it
Useful when you want a frontier chat assistant to write the brief and review the diff while Codex does multi-file implementation work, keeping the implementation load off the orchestrator's chat quota.
Requirements
Runs locally over stdio, typically via npx. Needs Node.js 20+ and the OpenAI Codex CLI installed and logged in (codex login). No environment variables or headers are declared.
Before you install
Delegated runs are auto-approved in every mode and can reach any file the user account can and the network; mode instructs rather than limits. Review the git diff after every run, and check status because a run that spawns then fails can still return normally. Codex usage is billed separately from the orchestrator's quota.

Installation

In SourceWeft

  1. Open Codex Delegate in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

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]

[Codex Delegate logo]

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.

⚡ 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, though the Codex side still bills its own way. 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, cumulative thread 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, cumulative thread token counts, and the threadId to continue from. Fields that carry no signal are omitted.
  • 📋 Plan first, then build it on the same thread — plan 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, Google Antigravity, GitHub Copilot CLI, Cursor and VS Code take it as a plugin, with a skill that teaches your agent how to delegate well. Cursor and VS Code install the server in one click; JetBrains, Devin Desktop (Windsurf), Visual Studio and the rest 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

shell
/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 to Cursor]

Or add it under Customize → MCPs in the sidebar, or in ~/.cursor/mcp.json (every project) or .cursor/mcp.json (this project):

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

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

Google Antigravity

shell
agy plugin install https://github.com/andreilungeanu/codex-delegate-mcp

Restart the Antigravity app to load it. If you added codex-delegate to mcp_config.json by hand, remove that entry.

Without the CLI, use the manual config under More clients.

GitHub Copilot CLI

shell
copilot plugin marketplace add andreilungeanu/codex-delegate-mcpcopilot plugin install codex-delegate@codex-delegate-mcp

The server alone, without the skill: copilot mcp add codex-delegate -- npx -y codex-delegate-mcp.

More clients

VS Code — one-click install, or .vscode/mcp.json

[Install in VS Code] [Install in VS Code Insiders]

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

Or run Chat: Install Plugin From Source with this repository's URL (needs the chat.plugins.enabled setting).

JetBrains AI Assistant — Settings → Tools → AI Assistant → MCP

Under Settings → Tools → AI Assistant → Model Context Protocol (MCP), click Add and paste this JSON:

json
{  "mcpServers": {    "codex-delegate": {      "command": "npx",      "args": ["-y", "codex-delegate-mcp"]    }  }}
Devin Desktop (formerly Windsurf) — ~/.config/devin/mcp_config.json

This config is for Devin Local, the default agent (Local 3.6+). On Windows the file is %APPDATA%\devin\mcp_config.json. Legacy Cascade and older Windsurf builds read ~/.codeium/windsurf/mcp_config.json.

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

Heads-up: Devin Desktop's Cascade agent caps you at 100 tools across all servers.

Visual Studio 2026 / 2022 — %USERPROFILE%\.mcp.json
json
{  "servers": {    "codex-delegate": {      "type": "stdio",      "command": "npx",      "args": ["-y", "codex-delegate-mcp"]    }  }}

Visual Studio 2022 needs 17.14+. Note the top-level key is servers, not mcpServers. A .mcp.json in the solution directory scopes it to that solution.

OpenCode — ~/.config/opencode/opencode.json or project opencode.json

OpenCode does not use mcpServers. Local servers go under mcp, with type: "local" and command as one array:

json
{  "$schema": "https://opencode.ai/config.json",  "mcp": {    "codex-delegate": {      "type": "local",      "command": ["npx", "-y", "codex-delegate-mcp"],      "enabled": true    }  }}

This is the v1 shape, which OpenCode v2 still reads (v2's native form is mcp.servers).

Google Antigravity (without the plugin) — ~/.gemini/config/mcp_config.json or workspace .agents/mcp_config.json
json
{  "mcpServers": {    "codex-delegate": {      "command": "npx",      "args": ["-y", "codex-delegate-mcp"],      "timeoutSeconds": 21660    }  }}
Kilo Code — kilo.jsonc (mcp key, not mcpServers)

Same shape as OpenCode: type: "local" and command as one array.

json
{  "mcp": {    "codex-delegate": {      "type": "local",      "command": ["npx", "-y", "codex-delegate-mcp"],      "enabled": true    }  }}

In the VS Code extension: Settings → MCP → Add Server → Local (stdio). On Windows, if npx is not found, use command cmd with arguments /c, npx, -y, codex-delegate-mcp.

Kiro and any other MCP client

Add the following server to the client's MCP config — for Kiro, ~/.kiro/settings/mcp.json (user) or .kiro/settings/mcp.json (workspace):

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

MIT © Andrei Lungeanu

Configuration · Security · Privacy · Terms · Changelog

Source: README.md at commit 90ace6e

Tools

3

delegate

Delegate coding task to Codex

Delegate a coding task to OpenAI Codex. Never run codex from the shell — use this tool. Check status before trusting result — a run that spawns then fails returns normally. Set spec, workspace and mode, plus resumeThreadId to resume and reviewTarget in review; leave every other field at its default unless the user asks. See the delegate skill.

ParametersfastmodespecrequiredmodeltimeoutMswebSearchworkspacerequiredreviewTargetresumeThreadIdreasoningEffort

cancel

Cancel Codex delegation

Cancel active runs. delegationId selects one (announced in progress before spawn — the only handle if a run wedges at startup), threadId all on its thread, neither all. Waits for settlement; if a process tree survives the kill deadline, it still returns and the delegate result warns. Status: cancelled, nothing-active, or not-found (no active run with this ID).

ParametersthreadIddelegationId

doctor

Diagnose Codex delegation setup

Diagnose plugin/CLI/login, recursion, and workspace (default: server cwd). deep adds no-quota help and model-catalog checks.

Parametersdeepworkspace

Version history

7
  1. v2.8.0LatestNov 8, 2026
  2. v2.7.0Nov 7, 2026
  3. v2.6.0Oct 22, 2026
  4. v2.5.0Oct 5, 2026
  5. v2.4.0Oct 4, 2026
  6. v2.3.0Sep 25, 2026
  7. v2.2.1Sep 16, 2026

Score

90% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 days25 pts
  • Auth declared10 pts

    Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.

  • Tools listedRequired15 pts
  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts