mcpField
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codex-bridge

codex-bridge

Local
xallindrome.coAI & Agents0Updated 1w ago

About codex-bridge

codex-bridge is an MCP server for using the Codex CLI from Claude Code to create plans and images. It saves each call as a disk-backed job that can be inspected, canceled, or resumed after interruption.

Key features

  1. 01Generate plans, design reviews, and second opinions
  2. 02Generate or edit images and collect outputs
  3. 03Run background jobs saved to disk
  4. 04Inspect, cancel, or resume jobs
  5. 05Run every call in a read-only sandbox

Use cases

  1. 01Ask Codex to plan implementation in the background
  2. 02Get image assets through Claude Code
  3. 03Collect job results after closing a session
  4. 04Resume interrupted jobs to finish image batches

MCP support

It serves MCP tools over stdio for Codex planning, image generation, result lookup, job resumption, and cancellation.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"xallindrome-labs-codex-bridge": {
"command": "npx",
"args": [
"-y",
"@xallindrome-labs/codex-bridge"
],
"env": {
"CODEX_BIN": "<CODEX_BIN>",
"CODEX_BRIDGE_HOME": "<CODEX_BRIDGE_HOME>",
"CODEX_BRIDGE_IDLE_TIMEOUT_MS": "<CODEX_BRIDGE_IDLE_TIMEOUT_MS>",
"CODEX_BRIDGE_PLAN_MODEL": "<CODEX_BRIDGE_PLAN_MODEL>",
"CODEX_BRIDGE_PLAN_EFFORT": "<CODEX_BRIDGE_PLAN_EFFORT>",
"CODEX_BRIDGE_IMAGE_MODEL": "<CODEX_BRIDGE_IMAGE_MODEL>",
"CODEX_BRIDGE_IMAGE_EFFORT": "<CODEX_BRIDGE_IMAGE_EFFORT>"
}
}
}
}
Run commandnpx -y @xallindrome-labs/codex-bridge
Environment variables to set
CODEX_BINPath to the Codex CLI binary. Auto-detected when unset.
CODEX_BRIDGE_HOMEWhere job files are stored. Default: ~/.codex-bridge
CODEX_BRIDGE_IDLE_TIMEOUT_MSStop a run after this many ms with no Codex output. Default: 600000
CODEX_BRIDGE_PLAN_MODELModel for codex_plan. Default: your Codex config.
CODEX_BRIDGE_PLAN_EFFORTReasoning effort for codex_plan. Default: your Codex config.
CODEX_BRIDGE_IMAGE_MODELModel for codex_image. Default: gpt-6-luna
CODEX_BRIDGE_IMAGE_EFFORTReasoning effort for codex_image. Default: high

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
npm@xallindrome-labs/codex-bridge0.1.0

Tools

5

Saved tool list · updated 1w ago

ParameterTypeRequiredDescription
cwdstringYesAbsolute path of the project directory Codex should inspect.
modelstringNoOptional Codex model override. Default: the user's Codex config.
effortenumNoOptional reasoning effort. Default: the user's Codex config (high). Use medium/low for quick questions; xhigh/max for hard architecture problems.low | medium | high | xhigh | max | ultra
contextstringNoOptional extra context: relevant diffs, error output, decisions already made.
requeststringYesWhat to plan or review. Include goals, constraints and acceptance criteria.
backgroundbooleanNoOptional. true = return a job_id immediately and keep working; collect the result later with codex_result. Default false (wait for the answer).
session_idstringNoOptional. Continue an earlier Codex thread instead of starting fresh.

Details

From the project README

codex-bridge

Codex jobs for Claude Code that survive crashes, closed windows and reboots, with Codex image generation built in. A dependency-free MCP server built Windows-first: every call is a job saved on disk, so you can close Claude, lose power, or kill a process, and pick the work up again with codex_resume.

Roles: Claude Code implements. Codex plans and builds images.

Recorded session: Claude Code starts codex-bridge and asks Codex for a plan

The server calls in this recording are real (Codex at effort: low, idle time trimmed); the claude mcp add line is scripted. The raw recording is docs/demo.cast; play it with asciinema play docs/demo.cast.

Quickstart

You need Node.js 20 or newer and the Codex CLI installed and logged in.

claude mcp add codex-bridge -- npx -y @xallindrome-labs/codex-bridge

Restart Claude Code, then ask it something like "Get a plan from Codex for adding rate limiting, in the background, and keep going". Claude will call codex_plan with background: true and collect the answer later.

Other MCP clients: run npx -y @xallindrome-labs/codex-bridge as a stdio server.

Platform note: developed and tested on Windows 11, where real Codex jobs have been run. CI checks on Linux, macOS and Windows (Node 20 and 22) that the server starts, speaks MCP and works when installed from the npm tarball, and on Linux and macOS that jobs run, finish and survive the server being killed, using a fake codex. CI has no real Codex CLI, so real Codex jobs on macOS and Linux are untested. Reports and fixes are welcome.

ToolWhat it doesSandboxDefault model / effort
codex_planCodex writes implementation plans, design reviews and second opinions. It inspects the project in cwd.read-only (always)Your Codex config defaults
codex_imageCodex generates or edits images. The bridge copies each one into output_dir as soon as it's made.read-only (always)gpt-6-luna / high
codex_resultGets a job's result or progress (wait_seconds up to 240), or lists recent jobs.
codex_resumeContinues an interrupted, timed-out or failed job from where it stopped.
codex_cancelStops a running job.

codex_plan and codex_image accept:

  • effort: low, medium, high, xhigh, max or ultra (Luna supports up to max).
  • model: overrides the default model for that call.
  • background: true: returns a job_id immediately so Claude can keep working.
  • session_id: continues an earlier Codex thread, for example "make the icon darker".

codex_image also takes count, the number of images wanted. Set it for batches: it enables k/count progress and resumes that ask for exactly the missing images.

How it compares

OpenAI's codex-plugin-cc is the official way to use Codex from Claude Code, and it's good at what it does: slash commands for review and rescue. codex-bridge is an MCP server instead, with a different focus: jobs that don't get lost, and images.

Several open issues in the plugin's tracker are about jobs getting lost, and codex-bridge is designed to avoid each of them. These come from reading the designs, not from a head-to-head test:

Reported in codex-plugin-ccHow codex-bridge handles it
Background job shows "running" forever after its worker dies (#704, #699)Status is worked out from files on disk plus a heartbeat and a process check. A dead runner shows as interrupted, never "running", and codex_resume continues it.
Windows cancel silently fails (#708)Cancel writes a marker file; the runner that owns the Codex process sees it within about 2 seconds and stops the process tree by calling taskkill.exe directly, with no shell in between.
Windows broker processes leak (#718, #782)There is no shared broker. Each attempt is one runner process that exits when Codex does.
One session ending kills other sessions' jobs (#671)Runners are started outside Claude's process tree (via WMI on Windows), so closing a session can't take them down.

What the plugin does that this doesn't: slash commands, and its review-gate and rescue workflows. And this one is newer, with far fewer users. If the plugin works for you, keep using it. If you've lost jobs, or want Codex to generate images that survive a crash, try this.

Jobs survive restarts

Every call is a job saved under ~/.codex-bridge/jobs/<job_id>/, including calls that aren't run in the background.

  • Claude closes or crashes: the job keeps running. server.mjs starts runner.mjs through WMI (Win32_Process.Create), so the job isn't part of Claude Code's process tree. Closing Claude can't kill it, and any later Claude session can collect it with codex_result.
  • The job itself dies (reboot, power loss, Codex crash, or killed process): the job is marked interrupted. The next Claude session is told about it when it starts. codex_resume continues it:
    1. It copies out any images generated just before the interruption.
    2. It resumes the same Codex thread: "N are already done, generate only the remaining ones."
    3. If no Codex thread had started yet, it reruns the original request.

How images are collected

Codex never writes image files. Its image tool stores every generated image in ~/.codex/generated_images/<thread>/. The runner checks that folder every 2 seconds and copies new images into output_dir as <filename>.png, <filename>-2.png, and so on, in the order they were made. copied.json in the job folder records what has been copied, so an image is never copied twice across attempts.

This gives three benefits:

  • Image jobs run in a read-only sandbox.
  • A crash loses at most the one image being generated.
  • Resume counts exactly what's done.

It also avoids a real problem: when Luna was allowed to save files itself, it re-typed each image as base64 through dozens of shell commands. That was slow, and the saved file no longer matched the original.

  • Codex stalls: the runner stops a run after 10 minutes with no output. The job is marked timed_out, and it can be resumed.

Each attempt keeps its own prompt.txt, events.jsonl (the Codex event stream), stderr.txt, heartbeat and result.json. Finished jobs are deleted after 14 days.

How it works

Each attempt runs codex exec --json (or codex exec resume <thread>) with the prompt on stdin. No shell is involved.

Every call runs read-only. New sessions pass -s read-only plus -c sandbox_mode="read-only"; resumed sessions pass -c sandbox_mode="read-only" (codex exec resume takes no -s). Your Codex config may default to danger-full-access, but that default never applies to bridge calls. The plan smoke test checks that a write attempted from a resumed session fails.

FileRole
server.mjsThe MCP server. It creates jobs, launches runners, works out job status from the files on disk, and handles resume and cancel.
runner.mjsRuns one attempt: starts Codex, records the heartbeat, watches for a stall or cancellation, collects images and writes result.json.
lib.mjsShared helpers: finding the Codex binary, building arguments, parsing events, handling images.

Install options

# for all your projects
claude mcp add -s user codex-bridge -- npx -y @xallindrome-labs/codex-bridge

# or from a local checkout
claude mcp add codex-bridge -- node /path/to/codex-bridge/server.mjs

Remove it with claude mcp remove codex-bridge (add -s user if you installed it that way).

Configuration (env vars)

VarDefault
CODEX_BINAuto-detected. It prefers a codex.exe next to codex-code-mode-host.exe, which is currently ~/.codex/plugins/.plugin-appserver/codex.exe.
CODEX_BRIDGE_HOME~/.codex-bridge
CODEX_BRIDGE_IDLE_TIMEOUT_MS600000 (stops a run after 10 minutes with no Codex output)
CODEX_BRIDGE_PLAN_MODEL / CODEX_BRIDGE_PLAN_EFFORTYour Codex config defaults
CODEX_BRIDGE_IMAGE_MODEL / CODEX_BRIDGE_IMAGE_EFFORTgpt-6-luna / high

Test

node smoke-test.mjs <scratch-dir> [plan|image|jobs|durable|all]

The smoke test drives the server over stdio like an MCP client and needs a logged-in Codex CLI; it uses a little of your Codex quota. The durable part uses taskkill, so it is Windows-only for now.

  • plan: runs a plan, then tries a write from a resumed session, which must fail.
  • image: generates one image.
  • jobs: tests background jobs, cancellation and the effort check.
  • durable:
    1. Kills the server while a job is running, then checks that a new server collects the result.
    2. Hard-kills an image batch partway through, then checks that a new server reports it as interrupted and that codex_resume finishes it.

Speed

Each call has a fixed cost of about 4–5 seconds, and changing settings barely moves it. The rest of the time is Codex thinking and generating, which takes seconds to minutes. To spend less time waiting, use background: true, a lower effort for quick questions, and include relevant code in context so Codex reads less of the project.

Notes

  • This uses Codex's own login and quota, with no separate API key. A job left running after Claude closes keeps using that quota until it finishes.
  • Bridge calls run headlessly, so they don't show up as conversations in the Codex Desktop sidebar.
  • Don't send secrets in prompts. Prompts go to OpenAI.

Issues and contributing

Bug reports and ideas are welcome on the issue tracker. Pull requests are welcome too, but reviewed slowly; see CONTRIBUTING.md. Please report security problems privately, as described in SECURITY.md.

License

MIT


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