Cloudish (https://cloudish.ai) runs a container from a Dockerfile, a source folder, or an existing
image and serves it at a live HTTPS URL. Images are built on Cloudish's servers, so no local Docker
daemon is needed. The agent creates its own API key with one unauthenticated call, and usage is paid
from that key's prepaid credits, which it can never exceed. A human can claim the key later to add
credits and see a dashboard. This skill makes the agent prepare the project, deploy it, report the
URL, and diagnose failures from real build and container logs.
Last updated 2026-10-21 (changelog).
Cloudish is an agent-first, API-key/credit, container-deployment platform: it
builds images server-side, so no local Docker or docker build is needed —
a local build is CPU/memory-heavy and often more than the machine you're on
can spare, and there's no registry to manage either way.
Cloudish hosts a private registry and runs the resulting containers with
attached storage. There is no user-facing product UX here — everything is
this API.
Never print API keys or secrets into chat, source code or logs. Never
report a deploy as succeeded until you've verified it: the build reachedsucceeded, and the app's logs (section 7) show it started and is
listening. Try its URL too if you can reach it, but some environments reach
cloudish.ai but not the apps' own domain, so a URL you can't
open isn't a failure by itself.
Creating a key itself needs no credential — every other call below
authenticates with the key it returns (`Authorization: Bearer
$CLOUDISHAPIKEY`). New keys include 0.1 credits to start, subject to availability. Mint new keys or delegate credits from one you have, as fits: a sub-agent
or container that needs its own credential gets a key under yours, funded by
transfer (credits.md).
curl -X POST https://cloudish.ai/api/v1/keys -H "content-type: application/json" \
-d '{"alias": "<project-name>", "agent": "<agent>", "model": "<model>", "ref": "skills-repo"}'
The key comes back in the response:
{ "apiKey": { "alias": "my-app", "balance": 0.1, ... }, "key": "cld_****", "claimUrl": "https://..." }
key authenticates every call below (`Authorization: Bearer
$CLOUDISHAPIKEY`). If this project already has one, reuse it instead of
minting another. Claiming is optional: claimUrl attaches this key to the
Cloudish account of whoever opens it and signs in, for a dashboard and
adding credits. It works once and expires in 30 minutes;GET /api/v1/credits/claim returns a new one (section 9).
alias is optional: the project's name makes a good one, or leave
it out for a random one. You get that name if it's free, or a close variant
(e.g. my-app-otter) if not; use the apiKey.alias that comes back, the{alias} in every project path below.
agent, model and ref are all optional; leave out any you don't know.agent is the product you run in (claude-code, claude, chatgpt,codex, cursor, grok, ...), model the model you are
(claude-opus-5-5, gpt-5.5, ...), and ref the plugin, directory or
link this document came from (claude-plugin, chatgpt-plugin,codex-plugin, mcp.so, producthunt, ...) — leave it out rather than
guess. They only show Cloudish which agents and channels use it. Keep ref as shown: it only tells Cloudish which link sent you here.
POST /api/v1/projects creates the project if it doesn't exist yet (or
updates it if it does — same call either way, so a redeploy script can
always call this unconditionally), and optionally attaches an image in the
same request. Two ways to attach one, mutually exclusive:
An image you already have — registered immediately:
curl -X POST https://cloudish.ai/api/v1/projects \
-H "Authorization: Bearer $CLOUDISH_API_KEY" -H "content-type: application/json" \
-d '{"name": "my-app", "image": "ghcr.io/acme/my-app:1.0.0", "port": 8080}'
# -> { "project": { "path": "your-alias/my-app", ... }, "app": { "status": "registered", ... },
# "subdomain": { "url": "https://<token>.cloudish.app/", ... } }
Build from source — upload a tar.gz build context (must contain aDockerfile at its root). The build runs server-side, not on your own
machine — send the context as-is rather than running docker build
locally first. Once it succeeds, the project's docker app is registered
automatically — no second call needed. This context is uploaded to Cloudish's own servers, the same as
any build-from-source platform — exclude anything secret-shaped from it
first (.env files, credentials, .git) and use section 2's encrypted
secrets endpoint for real credentials instead, never a file baked into the
context:
tar --exclude='.env*' --exclude='.git' -czf context.tar.gz .
curl -X POST https://cloudish.ai/api/v1/projects \
-H "Authorization: Bearer $CLOUDISH_API_KEY" \
-F "name=my-app" -F "port=8080" -F "context=@context.tar.gz"
# -> { "project": { "path": "your-alias/my-app", ... }, "build": { "id": 123, "status": "pending" } }
port defaults to 8080 and must be the port your server listens on,
whatever the Dockerfile's EXPOSE says: an nginx image listens on 80,
so send port=80 for one. Get it wrong and requests answer 503 with
"nothing accepts connections on port …".
The build runs with cpuCores: 3/memoryGb: 5 by default. If it dies
with no error beyond "Job has reached the specified backoff limit", that's
usually resource exhaustion rather than a Dockerfile problem — retry with
more of both as extra form fields, one of0.5, 1, 2, 3 cpu cores
(buildCpuCores) and 1, 2, 4, 5
GB memory (buildMemoryGb).
Poll until it settles:
curl https://cloudish.ai/api/v1/images/builds/123 -H "Authorization: Bearer $CLOUDISH_API_KEY"
# -> { "build": { "status": "running", "logs": "<build output so far>" }, "image": null }
build.logs is the current tail of what the build is doing — it grows on every
poll while the build runs, so print only the lines you haven't shown yet.
Stop once status is "succeeded" or "failed"; on "failed", show bothbuild.error and the tail of build.logs. Once "succeeded", the project's
docker app is already registered and its subdomain already provisioned — fetchGET https://cloudish.ai/api/v1/projects/{owner}/{name} for the resultingsubdomain.url, no separate subdomain call needed.
Other docker-app fields available on either path: env (JSON object of
non-secret vars), volumeEnabled/volumeSizeGb/volumeMountPath
(persistent storage), cpuCores/memoryGb (container size, distinct
from the build's own), maxBodyMb (the largest request body the app
accepts, 64 MB unless set, at most 1024; a bigger one gets 413
before it reaches the app, so raise it for large uploads). To run many isolated copies of the same app — one
sandbox per user, task or agent — see replicas.md.
Left out, a new app gets the default size, shared: billed for 0.1 CPU
and 0.2 GB, using up to 1 CPU and 1 GB when the machine has them
spare, and the first to restart when it runs short. Apps that must not
restart, run a database inside the container, or need their full memory all
the time (a Next.js server, Streamlit) run better on small or larger.
Left out on an existing app, its size stays as it is. The response's app.resources shows the size an app runs at and itscreditsPerHour. Sizes and pricing: instances.md.
Either way, unless this deployment has no run domain configured, the app is
already reachable — a permanent URL is provisioned automatically, returned
as subdomain.url above. It's https://<name>.cloudish.app/ and keeps working
whichever datacenter serves the app: save and share that one. See section 4 to swap the random URL for a
memorable one, rotate it, or turn it off.
Non-secret config goes in env on the same call as above:
curl -X POST https://cloudish.ai/api/v1/projects \
-H "Authorization: Bearer $CLOUDISH_API_KEY" -H "content-type: application/json" \
-d '{"name": "my-app", "image": "ghcr.io/acme/my-app:1.0.0", "port": 8080,
"env": {"LOG_LEVEL": "debug"}}'
Anything sensitive — API keys, tokens, passwords — is set separately here,
encrypted at rest, and merged into the container's environment
automatically. Never put these in env above, and never bundle them into
the build context in section 1 either:
curl -X PUT https://cloudish.ai/api/v1/projects/YOUR_ALIAS/my-app/secrets \
-H "Authorization: Bearer $CLOUDISH_API_KEY" -H "content-type: application/json" \
-d '{"name": "OPENAI_API_KEY", "value": "sk-..."}'
Request a volume when creating or updating the app:
curl -X POST https://cloudish.ai/api/v1/projects \
-H "Authorization: Bearer $CLOUDISH_API_KEY" -H "content-type: application/json" \
-d '{"name": "my-app", "image": "ghcr.io/acme/my-app:1.0.0", "port": 8080,
"volumeEnabled": true, "volumeSizeGb": 5, "volumeMountPath": "/data"}'
volumeSizeGb must be one of 1, 5 or 20; volumeMountPath defaults to/data. A volume can only attach to one container, so an app with one
can't run replicas.
Section 1 already provisioned a permanent URL automatically once the image
registered — subdomain.url in that response, or {identifier} below is a
random 32-character lowercase-hex string, unique by construction. This
section is for changing it afterwards, not for getting one in the first
place.
If the app is public-facing and a memorable name matters, set your own
instead (non-private projects only):
curl -X PUT https://cloudish.ai/api/v1/projects/YOUR_ALIAS/my-app/subdomain \
-H "Authorization: Bearer $CLOUDISH_API_KEY" -H "content-type: application/json" \
-d '{"label": "anamazingapp"}'
# -> { "subdomain": { "url": "https://anamazingapp.cloudish.app/", ... } }
label must be 1-63 characters: lowercase letters, digits and hyphens, not
starting or ending with a hyphen. A 503 on this call means this
deployment has no wildcard run domain configured. Names are global: a 409 means another datacenter's app already
has this one, so pick another. Leaked the URL? `POST
.../subdomain/rotate` issues a fresh one. Want the app unreachable from the
outside entirely (API-only)? DELETE .../subdomain tears it down; a later
redeploy will provision a new one automatically the same way the first did.
A request to the subdomain carries the same `Authorization: Bearer
$CLOUDISHAPIKEY as everything else in this doc; an open` (the default)
or public project also answers with no credential at all, billed to its
owner. This platform doesn't mediate identity for the container itself — no
trusted headers, nothing — that's the image's own job to configure if it
wants one. The container starts on first request if it isn't already, and
scales back down after inactivity
(30/60/300/900/3600/28800/86400 seconds, or 0 for never, keeping it
always on and billed around the clock; default is the deployment's own,
override per-key with `PATCH /api/v1/me {"settings": {"idleTimeoutSeconds":
A project can also answer at any number of domains you control. Add each
one (foobar.com, www.foobar.com, ...) to the same project:
curl -X POST https://cloudish.ai/api/v1/projects/YOUR_ALIAS/my-app/domains \
-H "Authorization: Bearer $CLOUDISH_API_KEY" -H "content-type: application/json" \
-d '{"host": "foobar.com"}'
# -> { "domain": { "host": "foobar.com", "status": "pending", "redirect": false,
# "txtRecord": { "name": "_cloudish-challenge.foobar.com", "value": "cloudish-verify=..." } } }
minute; once it matches, the domain turns active and stays that way.
It's only checked once, so the record can be removed afterwards.
CNAME for a subdomain likewww; an apex (foobar.com) can't be a CNAME at most providers, so use
an A record to that host's IP address (dig +short do.cloudish.ai), or your provider's
CNAME flattening/ALIAS if it has one. The certificate issues once both
steps are done.
app twice, add it with "redirect": true (or `PATCH
.../domains/www.foobar.com {"redirect": true}` later). It 308s to the
project's primary domain: its oldest active domain that doesn't
redirect, or its subdomain if there's none.
GET .../domains lists them; DELETE .../domains/{host} removes one. Each
active domain costs 0.01 credits a day. Adding one needs a positive
balance; at most 10 can be added per hour and 20 be pending at once. A409 means another project already holds that host.
A request to an out-of-credit project returns 402 (JSON) instead of
starting the container — a plain browser page load gets a 503 status page instead — see credits.md for adding credits, especially across
several projects. Ask the platform admin to grant more via POST /admin/v1/credits/grant,
or, for a sub-agent's key, get a hand from the parent key that minted it —
the parent transfers some of its balance to yours by alias, authenticating
with its own key, no admin needed:
`curl -X POST https://cloudish.ai/api/v1/credits/transfer -H "Authorization: Bearer
$PARENTAPIKEY" -H "content-type: application/json" -d
'{"to":"
Cloudish doesn't care what's inside the image — it just runs whatever
listens on port and reverse-proxies to it, adding no CORS headers of its
own: set them in your app if a browser on another origin calls it. How
containers are isolated: container.md. Bring any Dockerfile:
in standalone/server mode.
a quick data app or dashboard (bind to 0.0.0.0 and the port from
your own env var, not localhost, or the proxy can't reach it).
net/http server, Gin, or Echo — compiles to a singlestatic binary, which makes for the smallest, fastest-starting images.
Anything else that speaks HTTP on one port works the same way — these are
just the common cases.
Cloudish has no managed Postgres/MySQL offering — attach a volume (section
3) and run the database inside your own container instead:
under the mounted volume (e.g. $DATA_DIR/app.db). No extra process.
postgresql package to your image. On containerstart (not at build time), initialize a subdirectory of the mounted
volume with initdb if it isn't initialized yet, start the server withpg_ctl, then
idempotently create your role/database if missing (this runs on every
boot, so it has to be a no-op after the first). Run schema migrations at
startup too, since the database only exists once the container is
actually running. Recreate /var/run/postgresql before starting —
Kubernetes remounts /var/run as an empty directory on every container
start. Generate any long-lived secret (session signing key, etc.) once
and save it onto the same volume, so it survives restarts instead of
rotating every redeploy.
If your app needs to know who's visiting it, point it at Cloudish's own
OpenID Connect provider instead of running your own identity system — a
standard discovery document, Authorization Code + PKCE, no client secret
to manage:
GET https://www.cloudish.ai/.well-known/openid-configuration
Many off-the-shelf apps take this directly (e.g. a genericOIDC_ISSUER/OPENID_PROVIDER_URL setting) with zero code. If you're
writing the login flow yourself: redirect a signed-out visitor to
`https://www.cloudish.ai/oauth/authorize?clientid=code your callback receives at POST https://www.cloudish.ai/oauth/token
(with the PKCE verifier) for an id_token carrying sub/email/name.redirect_uri must be under your project's subdomain or one of its active
custom domains (section 4).
Build redirect_uri from the host the request came in on, not from a
fixed URL. An app can answer on more than one hostname (apps created before
their URLs moved to cloudish.app also keep their older*.on.<datacenter>.cloudish.ai one), and a sign-in has to come back to
the hostname it started on, where your app set its state cookie.
Your app's "Sign out" only ends your app's own session. To also let the
visitor sign out of Cloudish (so their next sign-in can pick another
account), send them afterwards to
`https://www.cloudish.ai/oauth/logout?idtokenhint=post_logout_redirect_uri (same rule as redirect_uri).
curl https://cloudish.ai/api/v1/images/registry -H "Authorization: Bearer $CLOUDISH_API_KEY"
curl -X DELETE "https://cloudish.ai/api/v1/images/registry/tags?repo=builds/123&tag=v1" \
-H "Authorization: Bearer $CLOUDISH_API_KEY"
Fetch the running container's own stdout/stderr on demand — pulled fresh
from the pod on every call, never persisted server-side, so polling it while
diagnosing an issue doesn't grow anything:
curl https://cloudish.ai/api/v1/docker/YOUR_ALIAS/my-app/logs -H "Authorization: Bearer $CLOUDISH_API_KEY"
# -> { "logs": "--- container logs ---\n...\n--- events ---\n..." }
Also includes the previous attempt's output if the container already
restarted once, plus recent Kubernetes events (ImagePullBackOff,FailedMount, ...) — often the actual explanation when a container never
gets far enough to write a log line at all.
Read credits.md when you perform credit operations — claiming,
transfers, or funding more than one project.
A key works fine unclaimed — claiming attaches it to a human's own account,
which unlocks a dashboard for it (usage, projects, balance) and a way to add
credits beyond the free grant. Whether and when that's worth doing is
situational: some deployments want a large balance up front, some are fine
running on the free grant for a while, some never need more. Bring it up
when it's relevant to what you and your human are doing, not on a fixed
schedule.
Credits are spent only while an app is in use: by default an app sleeps
after 15 minutes without requests (see section 4) and wakes on the next one.
More can be added at any time: through the claim link below (for a key
already in an account, from that account), or by a transfer from another
key. Deploy, /me and credits responses carryrunway: the balance and the creditsPerHour being spent.
GET /api/v1/credits/claim (same auth) mints a fresh, single-use link a
human can open to attach this key to their own account and add credits to
it. Run it yourself and give your human the resulting URL — not thecurl command for them to run:
curl https://cloudish.ai/api/v1/credits/claim -H "Authorization: Bearer $CLOUDISH_API_KEY"
# -> { "url": "https://www.cloudish.ai/claim?challenge=..." }
# -> tell your human: "To add credits to <alias>, open: https://www.cloudish.ai/claim?challenge=..."
The link works once and expires 30 minutes after it's minted, so mint it at
the moment you hand it over (the claimUrl from POST /api/v1/keys has
the same lifetime), and mention that it expires. If your human comes back
later, or the page says the link expired, just mint a new one — minting
never invalidates an earlier link that's still within its own lifetime.
Never hand over $CLOUDISH_API_KEY itself — the link alone is what proves
the claim, the raw key never needs to leave this session.
Every change to this document is listed in changelog.md.
The user says "Deploy this to Cloudish." The agent finds main.py serving on port 8000, writes a
Dockerfile that runs uvicorn main:app --host 0.0.0.0 --port 8000, points the database at/data/app.db, confirms with the user, and deploys with a volume:
# Build an inspected allowlisted staging directory outside the source tree first.
# Do not assume tar honors .dockerignore; exclude credential files, private data and symlinks.
tar -czf ../context.tar.gz -C ../approved-build-context .
curl -X POST https://cloudish.ai/api/v1/projects \
-H "Authorization: Bearer $CLOUDISH_API_KEY" \
-F "name=notes-api" -F "port=8000" -F "context=@../context.tar.gz" \
-F "volumeEnabled=true" -F "volumeSizeGb=1" -F "volumeMountPath=/data"
It polls the build, then reports the URL and that the database lives on the volume.
.env instead of creating a new one on every run.env.GET /api/v1/credits/claim, when they need to add credits; it works once and expires after 30 minutes.docker build locally first; send the build context as-is.references/ (or https://cloudish.ai/skill.md for the live copy) if a call is rejected.cloudish.ai and an API key with credits; once a project is out of credits, requests to it return HTTP 402 instead of starting the container.references/instances.md and https://cloudish.ai/skill.md for the live copy.references/changelog.md).risk: critical: the skill uploads project files to a third-party service, publishes an app to a public URL, and spends prepaid credits.DELETE /api/v1/projects/{alias}/{name}/subdomain, or rotate a leaked one with POST .../subdomain/rotate.0 (always on), and credit transfers..env*, .git, and other credential files from the build context; it is uploaded to Cloudish's servers.Solution: The server is probably bound to localhost or a different port. Bind to 0.0.0.0 on the port you sent, then redeploy.
Solution: Recreate /var/run/postgresql on container start and run initdb only when the data directory on the volume is empty.
Solution: The key was not saved. Always write it to .env immediately after creating it.
@dropthehassle-publish - For finished static sites rather than running containers.@docker-expert - For writing and optimizing the Dockerfile before deploying.