Landing page: https://codexify.dev/
Turn ChatGPT into a Codex-like coding environment — without using your Codex/Work quota.
Codexify gives a regular ChatGPT conversation the tools to work on your projects: file editing, terminal commands, Git, interactive diffs, and reusable skills. Describe a task, let ChatGPT inspect the code, make changes and run tests, then review the result — all from the same conversation.
ChatGPT does the reasoning; your machine runs the tools. Codexify connects them through Model Context Protocol (MCP), rather than running a Codex agent or starting a ChatGPT Work task. The normal workflow uses your ChatGPT allowance, leaving your Codex/Work quota untouched.
ChatGPT's own usage limits still apply. If you explicitly invoke Codex, Work, or another metered service through connected tools, that service's usage counts normally.
Get started · Documentation · Website · Downloads
Codexify runs inside an ordinary ChatGPT Chat, so the relevant limits are the Chat allowances rather than the Work/Codex quota. Codexify doesn’t use any Codex/Work quota, it only uses Chat quota which is independent:
| Plan | 5.6 Luna | 5.6 Sol | 5.6 Sol Pro | 6 Astra Pro | Context window |
|---|---|---|---|---|---|
| Free | ∞ | — | — | — | Varies |
| Go $8/month |
∞ | — | — | — | 256K |
| Plus $20/month |
∞ | ∞ High |
— | — | 256K |
| Pro 5x $100/month |
∞ | ∞ Extra High |
50/week1 | 50/week1 | 400K |
| Pro 20x $200/month |
∞ | ∞ Extra High |
1,190/week 170/day max |
200/week |
400K |
1 One shared 50-message weekly allowance across 5.6 Sol Pro and 6 Astra Pro.
Note: the context window is the total shared reasoning window, not the amount reserved exclusively for user input: system instructions, tools, memory, internal reasoning, and the response also consume it.
See OpenAI's Plan tiers details for more information.
- Explore, edit, and test. Search a codebase, apply patches, run your project's tests, and inspect the results.
- Review the work. See file changes in an interactive diff card, and exchange attachments and generated files with ChatGPT.
- Keep projects organized. Connect one repository or choose a project for each conversation. Optional Git worktrees keep concurrent edits in separate checkouts.
- Bring your conventions. Load
AGENTS.mdand skills, and save task notes and plans for later conversations. - Connect more tools. Make local or remote MCP servers available through the same connector, including servers configured in Codex.
Codexify runs on macOS, Linux, and Windows. You need a ChatGPT account or
workspace with custom MCP apps enabled
and access to OpenAI Secure MCP Tunnels
in an OpenAI Platform organization. ChatGPT access and tunnel permissions are
separate; a workspace administrator may need to grant them.
One Codexify service can connect to several ChatGPT accounts by configuring
separate tunnel ID/key-reference pairs in openaiTunnels; all accounts share
the same local tools and project access. See native tunnel setup.
macOS / Linux
curl -q -fsSL https://codexify.dev/install.sh | shWindows PowerShell
powershell -ExecutionPolicy ByPass -c "irm https://codexify.dev/install.ps1 | iex"The installer verifies the downloaded binary's checksum and adds it to your PATH.
When a config already exists it also refreshes the per-user background service;
on a first install, quickstart creates the config and installs the service. No
Rust toolchain is needed. Open a new terminal after installation so the
codexify command is available.
macOS release binaries use the stable Developer ID identity dev.codexify and
are published only after Apple accepts both Intel and Apple-silicon
notarizations. The first signed update from an older ad-hoc build may require one
final macOS privacy reapproval; later signed updates retain the same identity.
Prefer a manual install? Get a prebuilt binary or read the installation guide. The installer source is available for macOS/Linux and Windows.
codexify quickstartThe wizard defaults to multi-project mode, asks for the matching projects root or
single project directory, then guides you through creating a tunnel, its runtime
API key, and the Codexify connector in ChatGPT. It prints the links and exact
settings to use, saves your configuration, and starts the connection.
Keep Codexify running while you use it; the background service handles that for a
standard installation.
This setup uses an outbound OpenAI tunnel: you do not need a public server URL or an inbound port. For other deployments, see connection options. The fully populated configuration example shows every supported JSON field with non-secret placeholders.
Configuration schema changes are migrated automatically on the next successful
startup. Codexify validates the migrated document before replacing the config,
keeps a byte-for-byte *.before-schema-vN.bak copy beside it, preserves file
permissions, and refuses configs written for a newer schema version.
Start a regular Chat conversation in ChatGPT, not a Work or Codex task, and select the connector you created. If you enabled multiple projects, give ChatGPT the project path or choose one when asked. Start with a read-only request:
Call get_agent_brief and follow the project's instructions.
Explain how this project is organized. Do not change any files.
Then ask for a concrete change, for example:
Fix the failing test, run it again, and show me the diff. Do not commit yet.
A greeting leaves the setup project picker open; scratch is selected only by an explicit choice. Paste a GitHub repository/PR/branch/commit URL, search local projects, or use Worktrees to reuse an existing checkout. After selection, Switch to another project reopens the picker without deleting prior files. The agent receives the new path and must reload the project instructions. See the workspace guide for project selection and worktree options.
Steer an active conversation by appending to a local Markdown file instead of sending another ChatGPT message. Enable the feature in your Codexify config:
{
"agentChat": {
"enabled": true,
"maxWaitMs": 115000
}
}Restart Codexify, refresh the connector's tools in ChatGPT Settings, and start a
new conversation. get_agent_brief reports that conversation's CHAT.md path,
stored with project metadata outside the repository by default. Every
conversation has its own file, even when several use the same checkout.
With UI widgets enabled, setup opens one persistent chat panel beneath the
setup controls. Chat tools update it without opening more cards. Send with the
arrow button or Return; Shift+Return inserts a newline. One grey tick means saved
to CHAT.md, two grey ticks mean returned to the agent, and two blue ticks mean
acknowledged through chat_read, chat_write, or chat_await. The Agent indicator
shows online for calls under four minutes old, last seen from four to under ten minutes,
and offline thereafter. These are tool-activity receipts, not proof of model
comprehension. A small header total counts model-visible Codexify tool calls in
the conversation. Between agent messages, a compact counter shows the calls since
the previous agent message and increments live while the agent works. Widget
polling and other app-only helpers do not inflate either count. Widget sends do
not start a new ChatGPT turn.
To monitor all persisted chats outside ChatGPT, run codexify chat on the
computer running the service and open the printed URL. The standalone view
lists conversations by their latest chat entry, with activity state and an
unread dot, and reuses the widget's message history, composer, receipts, file
downloads, and tool counters. It connects to a separate localhost listener,
not the shared MCP tunnel. ChatGPT does not pass conversation titles to the
connector, so list titles are derived from chat entries (preferring the first
user entry). See the
standalone chat reference.
If agentChat.notifications is configured, the server also attempts one
notification when this indicator turns offline after 10 minutes without an agent
tool call. The next agent call re-arms the alert. This works without an open
chat card, but the Codexify service must be running; no alert is sent before the
first recorded agent call.
Messages show a small local HH:mm timestamp at the bottom right, before the
ticks on user messages. Earlier local calendar days also show YYYY-MM-DD
before the time. Dates follow the viewer's timezone and update at midnight.
The panel renders Markdown tables, reference links, nested lists, and code.
For files, use the chatLink returned by export_host_file in the agent's
Markdown message; supported hosts download it without starting another turn.
Older sandbox links work when they identify an unambiguous export in this workspace.
You can also append your instructions to the file and save. The agent uses chat_read,
chat_write, and chat_await; other tool results also deliver unread messages
without consuming them. Optional Apprise notifications send the agent's Markdown
to ntfy, Pushover, and other supported services through one URL-based configuration.
Notifications use only the local Apprise backend and require Python with Apprise
installed. Schema migration renames an existing markdownChat block to
agentChat and converts the former native ntfy child to an Apprise ntfy
service URL. The feature is disabled by default and does not guarantee unlimited
ChatGPT runtime or alter OpenAI's usage limits.
See Markdown chat configuration and semantics for notifications, timeouts, schema refreshes, and append-only editing rules.
Codexify runs real commands with your user account's permissions. Shell execution is unrestricted and has no command allowlist. Project boundaries and Git worktrees are not an operating-system sandbox, and commands can reach beyond the project.
Start with a trusted repository, review requested actions, and keep credentials out of chats and version control. A private tunnel keeps the MCP endpoint off the public internet; it does not make inference local. Code and tool results returned to ChatGPT are sent to OpenAI.
See the security reference for access controls, command restrictions, and the authority of connected MCP servers.
| Task | Command |
|---|---|
| Check configuration and connectivity | codexify doctor |
| Print or inspect configuration | codexify config · codexify config get <key> |
| Edit configuration | codexify config edit |
| Check the background service state | codexify service status |
| Follow the formatted service log | codexify service logs -f |
| Stop the background service | codexify service stop |
| Start it again | codexify service start |
| Restart it without changing login startup | codexify service restart |
To update a standard installation, ask ChatGPT to update Codexify. After the service restarts, open the connector in ChatGPT Settings and click Refresh at the bottom of its tool list. The update guide explains the process.
For setup problems, start with Troubleshooting. Report reproducible bugs in GitHub Issues.
| Looking for... | Read |
|---|---|
| Setup and usage guides | Wiki |
| CLI options, configuration, and tool behavior | Technical reference |
| Additional MCP servers and reusable workflows | MCP bridging · Skills |
| Building or contributing | Architecture · Development commands |
MIT. Codexify is an independent project, not affiliated with OpenAI.
These connect a ChatGPT conversation to tools on your machine, as Codexify does.
| Project | Focus |
|---|---|
| CodexPro | Local coding tools, attachment import, and handoff plans. |
| local-dev-mcp | Registered projects with file, Git, shell, browser, and mobile tools. |
| codex-free | Rust MCP bridge with coding tools, saved context, skills, and MCP aggregation. |
| chatgpt-web-oauth-mcp | OAuth connector with background jobs, terminal sessions, and optional CLI-agent delegation. |
| Agentic MCP | Structured editing, Git worktrees, semantic navigation, and checkpoints. |
| Local Coding Agent | MCP workspace with desktop tray apps, a dashboard, and browser-preview tools. |
These bring web-chat models into a coding client rather than making ChatGPT the primary interface.
| Project | Focus |
|---|---|
| codex-chatgpt-web | ChatGPT Web as selectable Codex models through an embedded browser, with optional access to the active Codex task's tools. |