codex-with-chatgpt

ChatGPT thinks. Codex works. ChatGPT 负责思考，Codex 负责干活。

中文 — ChatGPT 付费订阅的网页版额度大量闲置，Codex 却在消耗紧张的 API 额度做规划和 Review。本项目把"思考"交给你已付费的网页版 ChatGPT， Codex 只负责执行。不用 API Key、不搞逆向代理——官方网页 + 只读 MCP 桥接。

EN — ChatGPT Plus/Pro web quota sits idle while your coding agent burns scarce API/Codex tokens on planning and review. This project moves the thinking to the subscription you already pay for; Codex only executes. No API keys, no reverse proxy — official web UI plus a read-only MCP bridge.

中文 — 把 ChatGPT 网页版变成 Codex 编码会话的"规划与审查大脑"，执行权 完全保留在 Codex 手里。你的仓库永远不会被上传：ChatGPT 通过一条安全的、 OAuth 保护的只读 MCP 连接，按需读取当前工作区里它真正需要的那几行代码。

EN — Use the ChatGPT web app as the planning and review brain for your Codex coding sessions, while Codex keeps full ownership of execution. Your repository is never uploaded: ChatGPT reads exactly the lines it needs through a secure, OAuth-protected, read-only MCP connection to your current workspace.

Detailed docs below are in English · 详细中文文档见 README.zh-CN.md

中文 — 不懂 git、Node、终端？完全不需要懂。把下面这段话原样复制给你的 编码 Agent（Codex），然后去倒杯咖啡：

请帮我完整安装并配置 Codex with ChatGPT，全程自动，我是不懂技术的小白，
所有事情你自己做：

1. 环境自检：需要 git 和 Node.js ≥ 20，缺什么就自动安装
  （macOS 用 Homebrew，Windows 用 winget），同时安装 cloudflared。
2. 下载：把 https://github.com/XiaoDuoYa/codex-with-chatgpt 克隆到
   ~/codex-with-chatgpt（已存在就 git pull 更新）。
3. 构建：在该目录里执行 corepack pnpm install 和 corepack pnpm build。
4. 安装 Skill：先确定 Codex home：如果设置了非空的 CODEX_HOME 就使用它，
   否则使用 ~/.codex（Windows 默认为 %USERPROFILE%\.codex）。把仓库里的
   skill/SKILL.md 复制到 <codex-home>/skills/codex-with-chatgpt/SKILL.md，
   并把文件中 "The codex-with-chatgpt checkout lives at:" 那一行的路径改成实际克隆路径。
5. 首次配置：按 SKILL.md 里的 first-time setup 流程执行
  （运行 c2c setup，用内置浏览器打开 ChatGPT 配置连接器并输入配对码）。
   全程只用内置浏览器，禁止打开任何第三方浏览器。
6. 只有遇到需要我登录（ChatGPT / Cloudflare）、验证码或两步验证时才叫我，
   而且一次只告诉我一个动作。
7. 完成后给我看 ✓ 清单，并确认文件读取测试通过。我不懂 MCP、OAuth、
   Tunnel、端口这些词，不要向我解释；出了问题先自己修。

EN — Don't know git, Node, or terminals? You don't need to. Copy the paragraph below, paste it to your coding agent (Codex), and go grab a coffee:

Please install and configure "Codex with ChatGPT" for me, fully automatically.
I am a non-technical user — do everything yourself:

1. Check the environment: git and Node.js >= 20 must be available. Install
   anything missing yourself (macOS: Homebrew, Windows: winget). Also install
   cloudflared.
2. Download: clone https://github.com/XiaoDuoYa/codex-with-chatgpt into
   ~/codex-with-chatgpt (if it already exists, git pull to update).
3. Build: inside that folder run `corepack pnpm install` then `corepack pnpm build`.
4. Install the Skill: determine the Codex home first: use a non-empty CODEX_HOME
   when set, otherwise use ~/.codex (%USERPROFILE%\.codex on Windows). Copy
   skill/SKILL.md to <codex-home>/skills/codex-with-chatgpt/SKILL.md, and update
   the line "The codex-with-chatgpt checkout lives at:" to the actual clone path.
5. First-time setup: follow the SKILL.md "first-time setup" workflow
   (run c2c setup, configure the ChatGPT connector in the BUILT-IN browser,
   enter the pairing code). Never open a third-party browser.
6. Only interrupt me for logins (ChatGPT / Cloudflare), CAPTCHAs or 2FA —
   and give me exactly ONE action at a time.
7. When done, show me the ✓ checklist and confirm the file-read test passed.
   I don't know what MCP, OAuth, tunnels or ports are. Don't explain them.
   If anything breaks, fix it yourself first.

Updates · 更新 — The Skill checks GitHub once a day and updates itself when a new version is released; no action needed. You can also say "更新 Codex with ChatGPT" anytime. / Skill 每天自动检查一次 GitHub，有新版本会自动更新，无需任何操作； 也可以随时对 Codex 说"更新 Codex with ChatGPT"。

The sections below are in English. 以下详细内容为英文，中文完整版见 README.zh-CN.md。

Let <codex-home> be a non-empty CODEX_HOME when set; otherwise use ~/.codex (%USERPROFILE%\.codex on Windows).

1. Install the Codex Skill: copy skill/ to <codex-home>/skills/codex-with-chatgpt/.
2. Tell Codex: "Set up Codex with ChatGPT." (中文: "使用 Codex with ChatGPT 完成首次配置。")
3. Use Codex normally: "Use Codex with ChatGPT to implement XXX."

Installation scope: This repository does not publish or install a Codex Web GPT, launcher, or model-catalog entry. Installation consists of building this checkout, installing skill/SKILL.md as a Codex Skill, and running c2c setup to configure the ChatGPT connector. For Web GPT or model-catalog problems, see troubleshooting.

That's the whole manual. You don't need to know what MCP, OAuth, tunnels, ports or localhost are — Codex configures everything automatically and you just see:

Codex with ChatGPT

✓ Project detected
✓ Workspace Bridge started
✓ Secure connection established
✓ ChatGPT connected
✓ File read test passed

Ready.

The only steps that may need you: logging into ChatGPT (and, if you want a stable hostname, logging into Cloudflare once). A new workspace also asks you to create a ChatGPT Project (collection) once — pick project-only memory, name it after the workspace. If the sidebar has no Projects row, hover Chats, open the … menu, and choose Organize by project. Codex then saves that collection link and starts chats from that page. Existing workspaces that already have a C2C chat stay on the old one-conversation style until you ask to switch.

The default public address is a temporary Cloudflare URL. It changes when the bridge restarts, and Codex repairs ChatGPT by deleting that workspace's connector and adding it again.

If you have a Cloudflare account and a domain already on Cloudflare, first-time setup (and the next coding session, once) will ask whether you want a stable hostname such as c2c-<project>.your-domain.com. That path opens a browser so you can authorize Cloudflare. After that, the ChatGPT connector keeps working across restarts. If you skip it, or the login fails, Codex stays on the temporary address — same features, just a slower repair.

Credentials stay in the OS app state directory, not in the project.

             ┌───────────────────────────┐
             │       ChatGPT Web         │
             │  Reason / Plan / Review   │
             └──────────┬──────────▲─────┘
                        │          │
               MCP      │          │ Computer Use
            Data Plane  │          │ Control Plane (<1 KB messages)
                        ▼          │
             ┌─────────────────────┐
             │      C2C Bridge     │   loopback-only HTTP server
             │  read-only MCP      │   OAuth 2.1 + one-time pairing code
             │  OAuth + Pairing    │   Cloudflare Quick Tunnel
             │  Tunnel Manager     │
             └──────────┬──────────┘
                        │  read-only
                        ▼
             ┌─────────────────────┐          ┌─────────────────────┐
             │   Local Workspace   │◀─────────│    Codex Harness    │
             └─────────────────────┘ edit/git │ shell / tests / fix │
                                              └─────────────────────┘

• Control plane (Computer Use): Codex and ChatGPT exchange tiny structured [C2C] state messages — INIT → PLAN → EXECUTED → REVIEW → DONE. No diffs, no logs, no file bodies are ever pasted.
• Data plane (MCP): ChatGPT pulls what it needs itself through 10 read-only tools: workspace_info, list_directory, read_file, search_workspace, git_status, git_diff, test_status, execution_summary, execution_output, read_image.
• Independent review: after Codex executes, ChatGPT inspects the actual git diff and test records through MCP — it never trusts "all tests passed" claims blindly.

The connector remains read-only: read_image can inspect supported workspace images but cannot write files. After a requested image or video is downloaded through the visible ChatGPT UI, the local executor can validate and import the original with c2c asset import -w <workspace> --from <download> --to <new-path>. Imports are workspace-contained, signature-checked, size-limited, reject active SVG content, and never overwrite an existing file.

• Read-only by construction: write/delete/shell/commit tools simply do not exist on the server. No prompt injection can enable them.
• One workspace = one boundary: every token is bound to a single workspace; path containment uses canonical realpaths (symlink/..//absolute-path escapes are all blocked and tested).
• Sensitive files never leave: .env*, keys, SSH, credentials are denied by default (.env.example allowed); .c2cignore adds your own rules.
• Knowing the URL grants nothing: the public MCP endpoint requires OAuth 2.1 (PKCE S256, dynamic client registration, rotating refresh tokens). Without a token: 401. Wrong workspace: 403.
• The model never sees long-lived credentials: the only secret that ever touches a browser is a one-time pairing code (5-minute TTL, 5 attempts, rate-limited, destroyed on use).

Full threat model: docs/security.md

pnpm install
pnpm build          # -> dist/, exposes the `c2c` bin
pnpm test           # vitest: 150 tests (path security, OAuth, pairing, MCP e2e)

c2c setup           # bridge + tunnel + pairing code, all in one
c2c sandbox-allow   # whitelist the settings dir in Codex (macOS + Windows)
c2c status / doctor / pair / unpair / logs / stop

Requirements: Node.js >= 20, git. cloudflared for the public connection (auto-detected; the Skill installs it for you). If QUIC is blocked, set C2C_TUNNEL_PROTOCOL=http2 and restart the bridge.

Docs: architecture · protocol · security · troubleshooting

src/
  bridge/     loopback HTTP server, port recovery, admin API
  mcp/        9 read-only tools, stateless Streamable HTTP
  auth/       OAuth 2.1 (PKCE, DCR, refresh rotation, revocation)
  pairing/    one-time pairing codes (CSPRNG, TTL, rate limits)
  workspace/  path containment, sensitive-file policy, search, git
  tunnel/     TunnelProvider abstraction + Cloudflare Quick/Named Tunnel
  execution/  execution records for the review loop
  process/    daemon lifecycle
  cli/        the c2c CLI
skill/        the Codex Skill (the real UX layer)
tests/        unit + integration tests
docs/         architecture / protocol / security / troubleshooting

V1. Verified end-to-end: bridge, OAuth + pairing, public tunnel, ChatGPT connector setup, zero-touch first-run experience.

Unofficial community project. Not affiliated with or endorsed by OpenAI.

MIT