Is idapt Code a Codex-compatible CLI?

No. idapt Code is a curated skill in normal idapt Chat. It reaches the development environment through idapt's existing computer tools.

Can I import my Codex history?

Yes, one command: idapt chat import --from codex reads Codex CLI's rollouts and imports them with dates and tool calls. Dry-run first; the importer reports exactly what moved.

Does idapt Code have built-in worktrees or diff review?

No dedicated surface. The agent can use Git worktrees and show a diff through commands when the project needs them, but Codex has purpose-built worktree and review interfaces.

Can idapt Code work without GitHub?

Yes. It can work in any project directory reachable on the computer. Git delivery is optional and uses the repository remotes and provider tools already configured there.

Can I keep Codex and use idapt too?

Yes. idapt is an MCP server, so Codex or any MCP client can reach your idapt Drive, Knowledge, and computers. And when a non-GPT model tops the coding benchmarks, idapt's coding lane runs it: see /evals.

All comparisons

Agent platforms · Comparison

idapt Code vs OpenAI Codex

Codex connects terminal, IDE, GitHub, and cloud agents. idapt Code centers model choice and computers in normal Chat.

Last reviewed October 4, 2026

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Start free, no cardYour own keys work freeNo usage windowsNo training on your work by default

At a glance

OpenAI Codexidapt

Product shapeConnected CLI, IDE, desktop app, GitHub, and cloud agent surfacesA curated coding workflow inside normal idapt Chat

ModelsOpenAI models optimized for the Codex harnessAvailable hosted models, workspace provider connections, and compatible local models

Where code runsLocal sandboxed sessions and isolated OpenAI cloud environmentsA paired computer or an idapt cloud computer

Usage limitsChatGPT Pro and Codex meter usage with weekly caps that reset on a scheduleNo windows: platform usage bills transparent credits; your keys and local models uncapped

PrivacyOpenAI's terms govern Codex transcripts and outputs; check the current settings before pasting client workNo training on your work by default; BYOK and local lanes keep work on your terms

Parallel workMultiple agents, projects, worktrees, automations, and cloud tasksChat subagents, background work, and multiple independently selected computers

Git workflowBuilt-in change review, worktrees, GitHub connection, and pull-request flowsThe agent uses normal Git and provider CLIs on the selected computer

BYO computersYour local machinePair any machine you own, or provision idapt cloud computers

TunnelsExpose ports with separate toolingOne command exposes any port, SSH included

CredentialsEnv vars and local configCommand-scoped Secret injection, values never shown to agents

ContainersNo container managementDocker images and Compose files on your computers, secrets and backups included

AutomationsNot built-inScheduled delegated runs with bounded execution and traces

Moving inManual export scriptsOne command: idapt chat import --from codex, rollouts with dates and tool calls, dry-run first

Beyond codingExtensible with skills, plugins, SDK workflows, and broader agent tasksThe same Chat already includes files, models, agents, computers, media, and workspace tools

A check marks a row idapt wins, a cross marks a row OpenAI Codex wins.

What OpenAI Codex is great at

Codex is a mature coding-agent suite with a strong OpenAI coding model, local and cloud execution, IDE and GitHub handoffs, parallel agents, isolated worktrees, diff review, skills, automations, and enterprise controls. It is purpose-built for the software-development loop, and its worktree and diff-review surfaces are ahead of ours.

What idapt Code is great at

idapt Code does not create a separate coding command center. It gives normal idapt Chat a careful coding playbook and connects it to a paired or cloud computer. The value is continuity across models and workspace resources: use a local model where it fits, change models without changing the task surface, inject a workspace Secret into one command, expose the result through a tunnel, or continue with non-code work in the same product.

The limits question

Pro plans meter Codex usage in weekly windows that reset on a schedule, and a long agent run can stall at the cap. On idapt there are no limit windows: platform usage bills transparent credits at the prices shown in the app, your own keys and local models are uncapped, and a heavy week costs what it costs.

The privacy question

OpenAI's terms govern Codex transcripts and outputs, so check the current settings before pasting client work. On idapt, your work is not used for training by default, and on your own keys or a local model it runs on your terms entirely. idapt is hosted and not end-to-end encrypted; a paired machine plus a local model is the strongest isolation.

The verdict

Stay with OpenAI Codex if…

You want OpenAI's purpose-built coding harness, its connected CLI and IDE, built-in worktree and diff review, and GitHub-centered cloud delegation.

Choose idapt if…

You want a model-flexible coding workflow inside a broader AI workspace, no usage windows, and your own computer or an idapt cloud computer as the target.

Frequently asked

Explore the features

Computers

Daemon-connected machines with real filesystems and agent-friendly controls.

Cloud Computers

Spin up cloud machines your agents can use: per-second billing, torn down when idle.

Switching from OpenAI Codex?One command, dry-run first, with an import receipt. The migration guide shows exactly what moves and how.

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