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codex-imagegen-mcp

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codex-imagegen-mcp

An MCP server that generates images with the Codex CLI, so the work is billed to a ChatGPT subscription you already pay for instead of the per-image OpenAI API.

Why this exists

Claude Design can ask for images, but every image API call costs money on top of whatever you already pay OpenAI. A ChatGPT subscription can already generate images, and the official Codex CLI can drive it. What was missing was a way for an MCP client to reach that.

So: sign in to Codex once with your ChatGPT account, run one container, and point any MCP client at it. Images come back as URLs. Nothing here ever reads OPENAI_API_KEY — the Codex process's environment is built from an allowlist, so even if that variable is set on the host it is never forwarded. Spending the subscription is the entire point.

What you should know before relying on it:

  • One sign-in means one job at a time. A single ChatGPT session drives a single Codex process. The queue absorbs the backlog; it does not make the account faster.

  • An image takes 30 to 140 seconds. The MCP tool waits for you and reports progress, so clients do not have to poll.

  • Your account's terms and quotas apply. This automates the official CLI with your own credentials. It does not bypass anything, and it gives you no more capacity than your plan already has.

Related MCP server: imagengen

Quick start

One container. No database, no object storage, no message broker: with neither Redis nor S3 configured the process keeps its queue in memory and writes images to a volume, serving them from the same port it serves MCP on.

Requires Docker with the Compose plugin, and a ChatGPT account that can use Codex.

git clone https://github.com/tinyorbitvn/codex-imagegen-mcp.git
cd codex-imagegen-mcp
docker compose up -d

One step is left, because no image ships with credentials:

docker compose exec codex-imagegen-mcp codex login --device-auth

Follow the printed URL and code to sign in with your ChatGPT account. The container reports ready within a few seconds:

docker compose exec codex-imagegen-mcp codex login status

Now connect a client. For Claude Code:

claude mcp add --transport http imagegen http://localhost:8080/mcp

Any MCP client that speaks Streamable HTTP works the same way; the endpoint is POST /mcp and there is no session handshake.

Ask for an image and you get back a URL served by the same container. Stop it with docker compose down; add -v to throw away the sign-in and the images too.

The tools

Tool

What it does

create_image

Generates one image. Waits by default and reports progress; wait=false returns a job id immediately.

edit_image

Applies a change to an existing artifact as a NEW version. Never overwrites.

get_image_job

queued, running, completed, failed or cancelled, plus the artifact URL when done.

get_artifact

Artifact metadata and URL. Omit the version for the latest.

cancel_image_job

Cancels a queued or running job.

For animated web graphics, ask for each independently moving object in its own create_image call with isolated_object: true. A single combined scene cannot be split into layers afterwards.

Growing beyond one container

The same image runs three ways, chosen by the ROLE environment variable. all is the default and does everything in one process. mcp and worker split the endpoint from the Codex process, which lets you restart or scale the endpoint without touching the session that holds your ChatGPT sign-in.

Splitting needs a shared queue and shared storage, because two processes share neither memory nor a local disk. Set REDIS_URL and the S3_* variables and they replace the in-process queue and the local artifact directory. Each is independent: storage can move to S3 while the queue stays in the process.

Kubernetes

helm install imagegen ./charts/codex-imagegen-mcp \
  --namespace imagegen --create-namespace \
  --set publicBaseUrl=https://mcp.example.com

That is one pod, one volume for the sign-in and one for the images. Then sign in once inside the pod, the same way as above. See charts/codex-imagegen-mcp/README.md and docs/deployment-kubernetes.md.

The MCP endpoint authenticates nobody. Anything that can reach it can spend your ChatGPT quota. Keep it inside your network, or put an authenticating proxy in front.

Image

Published to GitHub Packages on every v* tag, public, no login needed:

docker pull ghcr.io/tinyorbitvn/codex-imagegen-mcp:latest

Documentation

Development

One npm package, no workspaces.

npm ci
npm run typecheck
npm test
docker build -t codex-imagegen-mcp:dev .

License

MIT. See LICENSE.

This server cannot be deployed

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Maintenance

ActivityMaintained
ResponsivenessNo issues

Resources

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