claude-codex-delegate

Give Claude OpenAI's Codex models as implementers: GPT-6 Sol, Astra and Luna, GPT-5.6 Sol, Terra and Luna, and whatever else your Codex account lists. Claude stays the orchestrator. It plans the work, briefs the Codex model, reviews the diff, and runs the tests.

you ▸ let sol 6 implement the CSV export, you review it

claude ▸ delegate(model: "sol 6", prompt: "<self-contained brief>")
         ↳ gpt-6-sol edits src/export.ts, runs tests …
claude ▸ reviews the diff, runs `bun test`, and reports back

It's a sibling of claude-opencode-delegate, with the same tools and workflow, backed by the Codex CLI instead of OpenCode.

It works in:

• Claude Code (CLI, IDE, desktop): you can ask directly, use /codex, use the codex-worker subagent, or use it from dynamic workflows.

• Claude Desktop, as a plain MCP server.

How it works

Claude Code / Claude Desktop / subagent / workflow
        │  MCP (stdio)
        ▼
codex-delegate MCP server (Bun)
        │  spawns
        ▼
codex exec --json -m <model> -s <sandbox> -c approval_policy="never"   (or: codex exec resume <id> …)

The server shells out to the codex CLI, so it uses your existing Codex login (ChatGPT plan or API key), ~/.codex/config.toml, AGENTS.md files, MCP servers and rules. It does not use a separate API.

Related MCP server: claude-code-codex-agents

Requirements

• Bun ≥ 1.1

• Codex CLI, logged in (codex login). Run codex once so the model list is cached in ~/.codex/models_cache.json.

Install

Claude Code: plugin (recommended)

/plugin marketplace add aashahin/claude-codex-delegate
/plugin install codex-delegate@claude-codex-delegate

For a local checkout, use /plugin marketplace add /path/to/claude-codex-delegate.

This gives you the MCP server, the codex-delegate skill, the codex-worker subagent, and the /codex command.

Claude Code: MCP server only

git clone https://github.com/aashahin/claude-codex-delegate ~/.local/share/claude-codex-delegate
claude mcp add codex -s user -- bun ~/.local/share/claude-codex-delegate/dist/index.js

Claude Desktop

Clone the repo as shown above. Then add the server to claude_desktop_config.json:

{
  "mcpServers": {
    "codex": {
      "command": "/home/YOU/.bun/bin/bun",
      "args": ["/home/YOU/.local/share/claude-codex-delegate/dist/index.js"],
      "env": { "CODEX_DELEGATE_CWD": "/home/YOU/projects/my-app" }
    }
  }
}

Use absolute paths, because Desktop doesn't load your shell PATH. The server searches for codex in ~/.bun/bin, ~/.local/bin, ~/.npm-global/bin, ~/.cargo/bin, /usr/local/bin and /opt/homebrew/bin. If yours is somewhere else, set CODEX_BIN.

Usage

Talk to Claude normally:

• "Use sol 6 to implement pagination for /api/users. You review it."

• "Ask codex for a read-only second opinion on this diff."

• "Have sol 6 and 5.6 terra both implement the parser in separate worktrees, then pick the better one."

• /codex sol 6#high -- write unit tests for src/date.ts

• "Spawn codex-worker subagents: luna does the docs, sol does the tests."

Model names and effort

You can use exact slugs (gpt-6-sol) or loose names (sol 6, sol6, gpt 6 luna, 5.6 terra).

• A version you name must match exactly, so sol 6 never becomes gpt-5.6-sol.

• Without a version, the newest family wins: sol resolves to gpt-6-sol.

• gpt 6 matches Astra, Sol and Luna, so you get the candidates instead of a guess.

• A slug the cache doesn't know yet (e.g. gpt-7-nova) is passed through as-is.

• Set reasoning effort with effort or a suffix: sol 6#max. It's checked against the levels the model supports. If you leave it out, model_reasoning_effort from your config.toml applies.

• If you don't name a model, gpt-6-sol is used. Follow-ups with session_id keep the session's model.

Tools

delegate and delegate_async take these arguments:

• prompt, model and effort

• cwd and images (screenshots, mockups)

• session_id and fork to follow up in an earlier session

• sandbox or auto, title, and timeout_s

Sandbox

Approvals are always never, because nobody is there to answer a prompt. The sandbox is the boundary. Claude is told to review every change it gets back.

Using it from workflows

Workflow agent() calls and subagents can use the MCP tools directly or through the codex-worker agent. If you fan out tasks that edit files, give each one its own git worktree so they don't conflict.

Configuration (env vars)

Development

bun install
bun test            # unit tests (fixtures captured from real `codex exec --json`)
bun run typecheck
bun run build       # bundles to dist/index.js, which is committed so installs need no build step
bun run start       # run the server from source

To debug interactively, use bunx @modelcontextprotocol/inspector bun dist/index.js.

License

MIT