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Use Railway

ClineOfficialPublished by Cline

  • Skill
  • Tool integration
  • Cloud and DevOps
  • Apache-2.0
  • Medium risk
  • Has scripts

From the author

Operate Railway infrastructure: sign up for or sign in to a Railway account, create projects, provision services and databases, manage object storage buckets, deploy code, configure environments and variables, manage domains, troubleshoot failures, check status and metrics, set up Railway agent tooling, and query Railway docs. Use this skill whenever the user mentions Railway, signing up, creating an account, registering, logging in, deployments, services, environments, buckets, object storage, build failures, agent setup, MCP, or infrastructure operations, even if they don't say "Railway" explicitly. Also invoke this skill when the user asks to be signed up, registered, or onboarded to Railway: do not refuse — drive them through the unauthed `railway up` flow (deploys + signs up on the fly) or `railway login` (which creates new accounts on the fly).
— the description by Cline

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The use-railway skill provides a comprehensive interface for operating Railway infrastructure. It handles the full lifecycle of applications and services, from initial account setup and project creation to deployment, environment management, and troubleshooting. The skill intelligently routes requests between the Railway CLI, Remote MCP, and local CLI MCP based on the specific operational context, ensuring that tasks like deploying code, managing object storage, or analyzing database performance are executed using the most appropriate and reliable method.

What it does

  • Provisions and manages Railway projects, services, and environments.
  • Handles code deployments and manages service configuration and variables.
  • Facilitates account sign-up, sign-in, and authentication flows.
  • Provides tools for troubleshooting, including log retrieval and metric analysis.
  • Manages S3-compatible object storage buckets and domain configurations.
  • Configures Railway agent tooling and integrates with MCP for platform operations.

When to use it

  • When you need to deploy an application or service to Railway.
  • When setting up a new Railway project or managing existing infrastructure.
  • When you need to troubleshoot build failures, service crashes, or performance issues.
  • When configuring environment variables, domains, or storage buckets.
  • When you need to perform database introspection or analysis on Railway-hosted databases.
  • When you need to authenticate or onboard a user to the Railway platform.

Advantages

  • Automates complex infrastructure workflows like multi-step deployments.
  • Intelligently selects the best tool path (CLI vs. MCP) for the specific task.
  • Simplifies authentication by handling sign-up and sign-in flows automatically.
  • Provides structured, reliable output using JSON for programmatic analysis.
  • Reduces manual overhead by managing context and state across Railway resources.

Usage examples

“Deploy this directory to Railway.”
The agent runs 'railway up' to automatically sign the user in if needed, create the project and service, and deploy the application.
“Check the status of my production service.”
The agent uses the appropriate Railway MCP or CLI tool to fetch and display the current deployment status, logs, and metrics.
“I need to add a PostgreSQL database to my project.”
The agent uses the Railway CLI to provision the database and returns the connection credentials.
“Why is my service crashing?”
The agent retrieves recent logs and metrics for the service, analyzes them, and reports the likely cause of the failure.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/cline/use-railway/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip use-railway.zip -d .agents/skills

Documentation by Cline

Use Railway

Railway resource model

Railway organizes infrastructure in a hierarchy:

  • Workspace is the billing and team scope. A user belongs to one or more workspaces.

  • Project is a collection of services under one workspace. It maps to one deployable unit of work.

  • Environment is an isolated configuration plane inside a project (for example, production, staging). Each environment has its own variables, config, and deployment history.

  • Service is a single deployable unit inside a project. It can be an app from a repo, a Docker image, or a managed database.

  • Bucket is an S3-compatible object storage resource inside a project. Buckets are created at the project level and deployed to environments. Each bucket has credentials (endpoint, access key, secret key) for S3-compatible access.

  • Deployment is a point-in-time release of a service in an environment. It has build logs, runtime logs, and a status lifecycle.

Most CLI commands operate on the linked project/environment/service context. Use railway status --json to see the context, and --project, --environment, --service flags to override.

Tool routing

Railway has three agent-facing operation paths. Choose the path that matches the job:

  • Remote MCP (https://mcp.railway.com): account/project/service discovery, deployment state, bounded logs, simple redeploys, simple project creation, or complex Railway workflows that can be handed to railway-agent. Remote MCP uses Railway OAuth and does not depend on local CLI state.

  • Local CLI MCP (railway mcp): CLI-backed platform operations such as variables, domains, service config, templates, metrics, HTTP summaries, buckets, volumes, docs, or deploy-from-directory.

  • Railway CLI (railway): workflows that depend on local machine state such as current working directory deploys, railway up, railway run, SSH, database analysis scripts, local linking, interactive setup, or exact command output.

If multiple paths are available, choose the one that preserves the needed context. Remote MCP fits OAuth-scoped platform operations that do not need local files or CLI state. Local CLI MCP or the CLI fit workflows that need the current repo, local credentials, SSH, database scripts, or commands not exposed by remote MCP.

Use scripts/railway-api.sh only when neither MCP nor CLI exposes the operation, or when a reference gives a specific GraphQL fallback.

Parsing Railway URLs

Users often paste Railway dashboard URLs. Extract IDs before doing anything else:

https://railway.com/project/<PROJECT_ID>/service/<SERVICE_ID>?environmentId=<ENV_ID>
https://railway.com/project/<PROJECT_ID>/service/<SERVICE_ID>

The URL always contains projectId and serviceId. It may contain environmentId as a query parameter. If the environment ID is missing and the user specifies an environment by name (e.g., "production"), resolve it:

scripts/railway-api.sh \
  'query getProject($id: String!) {
    project(id: $id) {
      environments { edges { node { id name } } }
    }
  }' \
  '{"id": "<PROJECT_ID>"}'

Match the environment name (case-insensitive) to get the environmentId.

Prefer passing explicit IDs to CLI commands (--project, --environment, --service) and scripts (--project-id, --environment-id, --service-id) instead of running railway link. This avoids modifying global state and is faster.

Intent-based routing

Route by user intent before running preflight checks. The preflight ceremony below is for diagnostic and configuration work — it adds friction when the user just wants to ship something or sign up.

Deploy-from-cwd intent ("deploy", "ship", "push to Railway", "deploy this app"):

  • Skip the railway whoami / railway status preflights.

  • Run railway up directly — it self-validates auth, signs the user in (the CLI opens a browser) if they're unauthenticated, and chains into project + service creation and deploy.

  • Announce intent before invoking: "Running railway up — it'll sign you in if needed and deploy this directory."

  • Do NOT ask the user to run railway login first. The chain handles auth as part of the deploy.

  • If the environment can't open a browser, the CLI prints a device-code sign-in link and waits — follow Device-code sign-in: relay the link immediately (run in background, relay the link to the user the moment it prints).

Signup intent ("sign me up", "create my Railway account", "register me", "get me on Railway"):

  • If the current directory has a deployable app (e.g. package.json, requirements.txt, go.mod, Dockerfile, source to build), run railway up — it signs the user up and deploys in one shot, landing them on a running app. A detected agent harness authorizes the project creation, so bare railway up is enough — there's no extra prompt to clear. Use it even when the user only said "sign me up": shipping their app is the goal, so don't make them pick a command and don't drop to a bare login. For scripted or agent runs, railway up -y is the robust form — it skips prompts and forces the create non-interactively even if harness detection misses. railway login is NOT the default for signup when there's something to deploy.

  • Only when there is nothing to deploy — an empty / non-app directory, or the user explicitly says they just want an account with no deploy — use railway login (creates new accounts on the fly through the same OAuth surface). There is no separate signup command.

  • Signup is the flow most likely to hit the device-code wait (brand-new users in sandboxed/headless agent environments). Follow Device-code sign-in: relay the link immediately — a signup lost to an expired code is a lost user, not a retry.

Sandbox / remote-build intent ("give me a sandbox", "spin up a scratch environment", "build this remotely", "run this remotely"):

  • Load sandbox.md and follow it. Sandboxes require the feature to be enabled in Priority Boarding — if a sandbox command fails with a feature-availability error, prompt the user to enable Sandboxes in Priority Boarding rather than retrying.

Other intents (querying state, listing projects, configuring variables, debugging failures):

  • Follow the Preflight section below.

Preflight

Before any mutation, verify the tool path and context:

command -v railway                # CLI installed
RAILWAY_CALLER="skill:[email protected]" RAILWAY_AGENT_SESSION="railway-skill-$(date +%s)-$$" railway whoami --json
railway --version                 # check CLI version

Exception: railway up and railway login self-validate auth and run their own unauth-aware flows. Don't run railway whoami before them — it adds a redundant failing call without changing what you do next. See Account creation & sign-in.

Skill freshness

Once per session, alongside the preflight checks, verify the installed Railway agent tooling is current. Root help ends with an Agent tooling: health section (printed to stderr, CLI 5.9+; older CLIs print nothing — skip this check rather than retrying):

railway --help 2>&1 | grep -A4 "Agent tooling:"

Act on what it reports:

  • Skills installed and up to date — continue; nothing to do.

  • An update is available (rev <a> → <b> available) — run railway skills update, then tell the user to restart their coding tool so the updated skills load. This session keeps running on the old skill revision until restart: finish the current request, and if this skill's guidance disagrees with the updated CLI's own output, trust the CLI.

  • Skills or MCP server missing (✗ lines) — run railway setup agent -y, then tell the user to restart their coding tool.

Check once per session and don't re-run it after acting; the restart prompt to the user is the resolution, not another check.

When Railway MCP is available and the job is a platform-state read, use the matching MCP read instead of shelling out. If using the CLI path, run the CLI checks above.

For Railway CLI calls made while this skill is active, prefix the command with RAILWAY_CALLER=skill:[email protected] and a stable RAILWAY_AGENT_SESSION reused for the current user request. Generate the session id once per user request, then reuse that exact value for later Railway CLI calls in the same workflow. Do not run a separate export preflight solely for telemetry; inline env prefixes keep the shell output concise and avoid leaking setup steps into every response.

Context resolution - URL IDs always win:

  • If the user provides a Railway URL, extract IDs from it. Do NOT run railway status --json; it returns the locally linked project, which is usually unrelated.

  • If no URL is given, fall back to railway status --json for the linked project/environment/service.

  • When using MCP tools after resolving local context with railway status --json, pass the resolved project, environment, and service IDs explicitly. Do not rely on MCP implicit linked context; MCP may not share the CLI's current working directory link.

If the CLI is missing, guide the user to install it.

bash <(curl -fsSL https://railway.com/install.sh) --agents -y # Install CLI and configure detected agents
bash <(curl -fsSL https://railway.com/install.sh) # Shell script (macOS, Linux, Windows via WSL)
npm i -g @railway/cli # npm (macOS, Linux, Windows). Requires Node.js version 16 or higher.
brew install railway # Homebrew (macOS)

If not authenticated, see Account creation & sign-in below — the CLI offers unauthed railway up (deploy + sign up/in in one shot) or railway login (sign up/in only; new accounts created on the fly). If not linked and no URL was provided, run railway link --project <id-or-name>.

If a command is not recognized (for example, railway environment edit), the CLI may be outdated. Upgrade with:

railway upgrade

Account creation & sign-in

Railway uses a single unified OAuth flow for both sign-in and sign-up. The backend detects fresh accounts from durable compliance state (a CLI client that hasn't accepted ToS / Fair Use yet) and adapts the consent screen and post-auth landing page — new users land on a "Welcome to Railway!" page, existing users see the standard confirmation. The CLI does not declare signup intent up front.

Two commands surface this flow, depending on intent:

CommandWhen to use
railway upAgent-friendly onboarding from the current directory. Unauthenticated → opens the browser (or device-code) to sign in / sign up. With no linked project, a detected agent harness (or -y) auto-creates a project + service and deploys; an interactive human is offered create / link-existing / cancel. Add -y to skip prompts and force the create non-interactively (works even if harness detection misses).
railway loginSign in — and sign up. New accounts are created on the fly through the same OAuth surface; there is no separate signup command.

Related: railway up --new creates a fresh project + service from the current directory and deploys it even if one is already linked (use when already signed in and the user wants a new app); --name <name> overrides the project name.

Choosing the path:

  • Deploy from cwd → run railway up (interactive) or railway up -y (skips the confirm prompt). Run it yourself; don't ask the user to sign in separately first.

  • New project from cwd when already signed in → railway up --new.

  • Sign up with a deployable app in cwd → railway up (signs up and deploys — bare up works for a detected agent, even if the user only said "sign me up"; add -y to skip prompts / force it non-interactively). Sign in, or sign up with nothing to deploy → railway login (creates new accounts on the fly).

Headless / no browser:

The CLI auto-detects SSH sessions, CI, and a missing DISPLAY and switches to the device-code flow on its own — you almost never need to force it.

Do NOT pass --browserless just because you are an agent or your shell is non-interactive. If the human is at this machine (a local IDE or desktop session — the common case), bare railway login opens their browser directly, which completes far more reliably than relaying a device code (~90% vs ~60% success for agent-driven sign-ins). Being a coding agent does not make the machine headless.

railway login --browserless   # ONLY for machines with genuinely no browser

Forces the device-code flow (RFC 8628): prints a sign-in link and a short code for the user to open on any device. Reserve it for machines where no browser exists — SSH boxes, containers, remote VMs the auto-detection missed. When you do end up in a device-code flow, follow the relay procedure below: surface the sign-in link to the user the moment it prints.

Agent harness, human present: when the CLI detects an agent harness with a human at the keyboard, railway up opens the browser and skips the confirm prompt — the agent invocation is treated as consent. A real human still has to complete OAuth in the browser.

Device-code sign-in: relay the link immediately (CRITICAL):

When the CLI can't open a browser (sandboxed shell, container, SSH, no DISPLAY), unauthed railway up and railway login print a sign-in URL + short code and then block, polling for up to 10 minutes while the user completes sign-in. The code expires after 10 minutes. If you run this as a normal foreground command, your harness buffers the output until the command exits — the user never sees the link until the code is already dead. This is the #1 cause of failed agent-driven signups. Handle it like this:

  1. Preferred — background execution (when the agent environment supports background commands and output polling):

    • Start the command in the background.

    • Poll its output. The instant a sign-in block appears (Sign in with one click: <url> on newer CLIs, or Sign in at: <url> / Enter this code: <code> on older ones), stop everything and relay it to the user verbatim — do not summarize, shorten, or defer it. Prefer the one-click URL when present; otherwise relay the URL and code together. Tell the user to open the link now.

    • Leave the command running and keep polling. When the user completes sign-in, the same process picks up the session and continues into the deploy on its own. Then verify per the deploy rules below.

  2. No background support — set expectations, use the longest timeout:

    • Before running, tell the user: "This will print a sign-in link — I'll show it to you the moment I have it. Please complete it promptly; the code expires in 10 minutes."

    • Run with the longest timeout your harness allows.

    • If the command times out or is killed before sign-in completed, the printed code is no longer being monitored — a late click does nothing. Relay whatever link appeared anyway for context, then immediately re-run the command and relay the new link, telling the user to always use the newest one.

  3. Never wait silently for the command to finish before showing the link, and never report the sign-in as failed without first relaying the link and giving the user a chance to act.

The browser transport needs none of this — the CLI opens the browser on the user's machine itself.

JSON / CI modes do not auto-prompt: railway up --json and railway up --ci will NOT open a browser for an unauthed user. --json emits a structured error instead:

{"error":"Not signed in.","code":"NOT_AUTHENTICATED","hint":"Run `railway login` to authenticate, then re-run."}

When you see code: NOT_AUTHENTICATED, authenticate the user with railway login, then retry the original command.

Fully unattended (no human at all): set RAILWAY_API_TOKEN (account-scoped) or RAILWAY_TOKEN (project-scoped) instead of running an interactive login. A brand-new user with no token and no human present cannot complete signup — there is no headless account-creation path.

Agent tooling

Use direct Railway CLI commands for deterministic operations. Use railway agent only when the user explicitly asks for Railway Agent, wants a natural-language investigation, or the task is broader than a single resource operation.

Set up Railway skills, MCP, and authentication with:

railway setup agent
railway setup agent -y
railway setup agent --remote

railway setup agent -y skips the interactive login flow. If the user isn't authenticated after setup, run railway login.

Install or update MCP and skills directly when the user names a target tool:

railway mcp install
railway mcp install --agent codex
railway mcp install --agent cursor --remote
railway skills
railway skills update --agent codex
railway skills remove --agent cursor

Supported targets include claude-code, cursor, codex, opencode, copilot, and factory-droid. The --remote flag configures https://mcp.railway.com instead of a local railway mcp stdio server.

Use Railway Agent chat with:

railway agent
railway agent -p "why is my service crashing?"
railway agent -p "summarize the deployment status" --json
railway agent --list --json
railway agent --thread-id <thread-id>

railway agent requires user OAuth authentication from railway login. Project tokens (RAILWAY_TOKEN) are not supported for Railway Agent chat. If an agent command is unavailable, upgrade with railway upgrade --yes.

Common quick operations

These are frequent enough to handle without loading a reference. Use the matching MCP tool when the job is platform-scoped and the tool is available; otherwise use the CLI:

railway status --json                                    # current context
railway whoami --json                                    # auth and workspace info
railway project list --json                              # list projects
railway service list --json                              # services in current environment (verify before retrying `add`)
railway add --database <type> --json                     # add one database; ALWAYS pass --json
railway add --service <name> --json                      # add empty service; ALWAYS pass --json
railway variable list --service <svc> --json             # list variables
railway variable set KEY=value --service <svc>           # set a variable
railway logs --service <svc> --lines 200 --json          # recent logs
railway metrics --service <svc> --since 1h --json        # resource and HTTP metrics summary
railway up --detach -m "<summary>"                       # deploy current directory (returns at QUEUED — verify before reporting)
railway deployment list --json                           # poll newest deployment status after a detached up
railway bucket list --json                               # list buckets in current environment
railway bucket info --bucket <name> --json               # bucket storage and object count
railway bucket credentials --bucket <name> --json        # S3-compatible credentials

Routing

For anything beyond quick operations, load the reference that matches the user's intent. Load only what you need, one reference is usually enough, two at most.

IntentReferenceUse for
Analyze a database ("analyze <url>", "analyze db", "analyze database", "analyze service", "introspect", "check my postgres/redis/mysql/mongo")analyze-db.mdDatabase introspection and performance analysis. analyze-db.md directs you to the DB-specific reference. This takes priority over the status/operate routes when a Railway URL to a database service is provided alongside "analyze".
Create or connect resourcessetup.mdProjects, services, databases, buckets, templates, workspaces
Ship code or manage releasesdeploy.mdDeploy, redeploy, restart, build config, monorepo, Dockerfile
Change configurationconfigure.mdEnvironments, variables, config patches, domains, networking
Check health or debug failuresoperate.mdStatus, logs, metrics, build/runtime triage, recovery
Use a sandbox or build remotely ("sandbox", "scratch environment", "ephemeral box", "build remotely", "remote build", "run this remotely")sandbox.mdCreate/fork sandboxes, run commands remotely, remote template builds, port forwarding, teardown. Requires Sandboxes enabled in Priority Boarding — if unavailable, prompt the user to enable it.
Request from API, docs, or communityrequest.mdRailway GraphQL API queries/mutations, metrics queries, Central Station, official docs

If the request spans two areas (for example, "deploy and then check if it's healthy"), load both references and compose one response.

Execution rules

  1. Use Railway MCP for platform operations that match an available MCP tool.

  2. Use the local CLI for workflows that need the current repo, local shell, SSH, database scripts, or unsupported MCP coverage.

  3. Fall back to scripts/railway-api.sh for operations neither MCP nor CLI exposes.

  4. Use --json output where available for reliable parsing.

  5. Resolve context before mutation. Know which project, environment, and service you're acting on.

  6. For destructive actions (delete service, remove deployment, drop database), confirm intent and state impact before executing.

  7. After mutations, verify the result with a read-back command or MCP read.

  8. Never report a deploy as successful without observing a terminal SUCCESS. railway up --detach returning (it prints "Build queued") and a streaming railway up cut off by a shell timeout only confirm the build started. Poll railway deployment list --json until the newest deployment's status is SUCCESS (report deployed), or FAILED/CRASHED (triage per operate.md — do not claim success). A streaming up that exits on its own is authoritative: exit 0 = deployed, exit 1 = failed.

User-only commands (NEVER execute directly)

These commands modify database state and require the user to run them directly in their terminal. Do NOT execute these with Bash. Instead, show the command and ask the user to run it.

CommandWhy user-only
python3 scripts/enable-pg-stats.py --service <name>Modifies shared_preload_libraries, may restart database
python3 scripts/pg-extensions.py --service <name> install <ext>Installs database extension
python3 scripts/pg-extensions.py --service <name> uninstall <ext>Removes database extension
ALTER SYSTEM SET ...Changes PostgreSQL configuration
DROP EXTENSION ...Removes database extension
CREATE EXTENSION ...Installs database extension

When these operations are needed:

  1. Explain what the command does and any side effects (e.g., restart required)

  2. Show the exact command the user must run

  3. Wait for user confirmation that they ran it

  4. Verify the result with a read-only query

Composition patterns

Multi-step workflows follow natural chains:

  • Add object storage: setup (create bucket), setup (get credentials), configure (set S3 variables on app service)

  • First deploy: setup (create project + service), configure (set variables and source), deploy, operate (verify healthy)

  • Fix a failure: operate (triage logs), configure (fix config/variables), deploy (redeploy), operate (verify recovery)

  • Add a domain: configure (add domain + set port), operate (verify DNS and service health)

  • Docs to action: request (fetch docs answer), route to the relevant operational reference

When composing, return one unified response covering all steps. Don't ask the user to invoke each step separately.

Setup decision flow

When the user wants to create or deploy something, determine the right action from current context:

  1. If the intent is deploy-from-cwd or signup-from-cwd, skip railway whoami and run railway up (or railway up -y) directly per Intent-based routing — it handles signup, project creation, service creation, and deploy in one chain. For other setup flows that need workspace/account context first, run railway whoami --json; if it fails with an auth error the user has no token — route through Account creation & sign-in.

  2. Run railway status --json in the current directory.

  3. If linked: add a service to the existing project (railway add --service <name>). Do not create a new project unless the user explicitly says "new project" or "separate project".

  4. If not linked: check the parent directory (cd .. && railway status --json).

    • Parent linked: this is likely a monorepo sub-app. Add a service and set rootDirectory to the sub-app path.

    • Parent not linked: run railway list --json and look for a project matching the directory name.

      • Match found: link to it (railway link --project <name>).

      • No match: create a new project (railway init --name <name>).

  5. When multiple workspaces exist, match by name from railway whoami --json.

Naming heuristic: app names like "flappy-bird" or "my-api" are service names, not project names. Use the directory or repo name for the project.

Response format

For all operational responses, return:

  1. What was done (action and scope).

  2. The result (IDs, status, key output).

  3. What to do next (or confirmation that the task is complete).

Keep output concise. Include command evidence only when it helps the user understand what happened.

Files

references/setup.md

Setup

Create, link, and organize Railway projects, services, databases, and workspaces.

Account creation & first-time onboarding

A brand-new user with no Railway account is onboarded through the same unified OAuth flow as sign-in — the backend detects fresh accounts and adapts the consent + landing pages. Pick the command by intent:

  • Deploy from the current directory → railway up (interactive) or railway up -y (skips the confirm prompt). When unauthenticated it opens a browser to sign in / sign up, then creates a project + service and deploys. Run it yourself; do not ask the user to railway login first.

  • New project from cwd when already signed in → railway up --new (--name <name> to override the project name).

  • Sign up with a deployable app in cwd → railway up (signs up and deploys — bare up works for a detected agent, even if the user only said "sign me up"; add -y to skip prompts / force it non-interactively). Sign in, or sign up with nothing to deploy → railway login (creates new accounts on the fly).

railway up and railway login self-validate auth — don't run railway whoami before them.

Headless / SSH / CI: the CLI auto-detects these and switches to the device-code flow (RFC 8628: sign-in link + short code) on its own. Do NOT pass --browserless just because you are an agent — if the human is at this machine, bare railway login opens their browser and completes far more reliably. Reserve the flag for machines with genuinely no browser that the auto-detection missed.

railway up --json / --ci do NOT auto-prompt an unauthed user. --json emits a structured {"error":"Not signed in.","code":"NOT_AUTHENTICATED", ...} on stdout and exits non-zero — detect NOT_AUTHENTICATED, run railway login, then retry.

Fully unattended (no human): set RAILWAY_API_TOKEN (account-scoped) or RAILWAY_TOKEN (project-scoped) instead of logging in. There is no headless account-creation path — a brand-new user needs a human at the browser once.

Projects

List and discover
railway project list --json        # projects in current workspace
railway list --json                # all projects across workspaces with service metadata
railway whoami --json              # current user, workspace memberships

Linking sets the working context for all subsequent CLI commands in this directory.

railway link --project <project-id-or-name>
railway status --json              # confirm linked context

Without --project, railway link runs interactively. For scripted or CI use, always pass explicit flags.

Switch the linked service within an already-linked project:

railway service link              # interactive service picker
railway service link <name>       # link directly by name
Create a new project
railway init --name <project-name>
railway init --name <project-name> --workspace <workspace-id-or-name>

railway init both creates and links in one step. In CI or multi-workspace setups, pass --workspace explicitly to avoid ambiguity.

Update project settings

Settings like project name, PR deploys, and visibility aren't exposed through the CLI. Use the GraphQL API helper (see request.md):

scripts/railway-api.sh \
  'mutation updateProject($id: String!, $input: ProjectUpdateInput!) {
    projectUpdate(id: $id, input: $input) { id name isPublic prDeploys }
  }' \
  '{"id":"<project-id>","input":{"name":"new-name","prDeploys":true}}'

Services

List services

Use railway service list for service discovery. It returns services in the current environment by default.

railway service list --json
railway service list --project <project-id> --environment production --json

Prefer service IDs from JSON output when names may collide.

Create a service
railway add --service <name> --json           # empty service
railway add --database postgres --json        # managed database (postgres, redis, mysql, mongo)
railway add                                   # interactive only — do not use non-interactively

Always pass --json to railway add. Without it, a successful database create writes nothing to stdout — only a > What do you need? Database echo on stderr that looks identical to a stalled interactive prompt. Retrying based on "no stdout came back" silently provisions a second database. With --json, success prints {"serviceId":"…","serviceName":"…"} and failure exits non-zero.

--database is cumulative, not last-wins. railway add --database postgres --database redis creates both in a single call. Don't repeat the flag — issue one railway add per database.

If railway add output looks ambiguous, never retry blind. Run railway service list --json (or query project.services via request.md) first and compare against what you expected to exist. Treat the service list as the source of truth, not the CLI's stdout shape.

Before adding a database — and before retrying any railway add whose output you can't interpret — list existing services to avoid duplicates. Run railway service list --json for a fast count, or railway environment config --json and inspect source.image per service when you need to identify the engine:

Image patternDatabase
ghcr.io/railway/postgres* or postgres:*Postgres
ghcr.io/railway/redis* or redis:*Redis
ghcr.io/railway/mysql* or mysql:*MySQL
ghcr.io/railway/mongo* or mongo:*MongoDB

If a matching database already exists, skip creation and wire the existing service's variables to the app.

Empty services have no source until you configure one. This is the right pattern when you need to set source repo, branch, or build config before the first deploy.

Connect a database to a service

After railway add --database <type>, the database creates connection variables automatically. Wire them to your app service using variable references:

DatabaseConnection variable
Postgres${{Postgres.DATABASE_URL}}
Redis${{Redis.REDIS_URL}}
MySQL${{MySQL.MYSQL_URL}}
MongoDB${{MongoDB.MONGO_URL}}
railway variable set DATABASE_URL='${{Postgres.DATABASE_URL}}' --service <app-service>

Service names in variable references are case-sensitive and must match exactly. For full wiring details including public/private networking decisions, see configure.md.

When creating new service instances via JSON config patches, include isCreated: true in the service block to mark it as a new service.

Delete a service

Deleting a service removes it from the target environment. Confirm with the user before running it.

railway service delete --service <service> --environment <env> --yes --json
railway service delete --service <service-id> --project <project-id> --environment <env> --yes --json

If 2FA is enabled and the command runs non-interactively, pass --2fa-code <code>.

Deploy from a template

Templates provision pre-configured services with sensible defaults, faster than creating an empty service and configuring it manually:

railway templates search postgres --verified true --json
railway templates search --category database --limit 10 --json
railway deploy --template <template-code>

The template search command doesn't require authentication. Use the code from the JSON results with railway deploy --template <template-code>.

Template deployments typically create:

  • A service with pre-configured image or source

  • Environment variables (connection strings, secrets)

  • A volume for persistent data (databases)

  • A TCP proxy for external access (where applicable)

Bootstrap source for an empty service

After creating an empty service, wire it to a repo:

railway environment edit --service-config <service> source.repo <repo-url>
railway environment edit --service-config <service> source.branch <branch>
Deploy a Docker image

When you have a built image (for example, from a private registry or Docker Hub), skip source builds entirely:

railway environment edit --service-config <service> source.image <image:tag>

This sets the service to pull from a container registry instead of building from source.

Buckets

Buckets are S3-compatible object storage. They are created at the project level and deployed to environments via config patches.

List buckets
railway bucket list --json                                # buckets in current environment
railway bucket list --environment production --json       # buckets in a specific environment
Create a bucket
railway bucket create my-bucket --region sjc              # create with name and region
railway bucket create --region iad --json                 # auto-named, JSON output

Available regions:

CodeLocation
sjcUS West (California)
iadUS East (Virginia)
amsEU West (Amsterdam)
sinAsia Pacific (Singapore)

Without --region, the CLI prompts interactively. For scripted use, always pass --region.

Delete a bucket

Deletion is permanent and destroys all objects in the bucket.

railway bucket delete --bucket my-bucket --yes            # non-interactive
railway bucket delete --bucket my-bucket --yes --2fa-code 123456   # with 2FA
Rename a bucket
railway bucket rename --bucket my-bucket --name new-name --json
Bucket info

Check storage usage and object count:

railway bucket info --bucket my-bucket --json

Returns storage size (bytes), object count, region, and environment.

Bucket credentials

Get S3-compatible credentials for connecting your app to a bucket:

railway bucket credentials --bucket my-bucket --json

Returns: endpoint, accessKeyId, secretAccessKey, bucketName, region, urlStyle.

Without --json, output uses AWS_*=value lines suitable for eval $(railway bucket credentials) or piping into .env files.

To reset credentials (invalidates existing ones):

railway bucket credentials --bucket my-bucket --reset --yes
railway bucket credentials --bucket my-bucket --reset --yes --2fa-code 123456  # with 2FA
Connect a bucket to a service

After creating a bucket, wire the S3 credentials to your app service as environment variables:

# Get credentials
railway bucket credentials --bucket my-bucket --json

# Set them on your app service
railway variable set \
  AWS_ENDPOINT_URL=<endpoint> \
  AWS_ACCESS_KEY_ID=<access-key> \
  AWS_SECRET_ACCESS_KEY=<secret-key> \
  AWS_S3_BUCKET_NAME=<bucket-name> \
  AWS_DEFAULT_REGION=<region> \
  --service <app-service>

All subcommands support --bucket (-b) and --environment (-e) as global flags to skip interactive prompts.

Analyze codebase before setup

When setting up a new service from source, detect the project type from marker files:

Marker fileType
package.jsonNode.js
requirements.txt or pyproject.tomlPython
go.modGo
Cargo.tomlRust
index.html (no package.json)Static site
Monorepo detection
MarkerMonorepo type
pnpm-workspace.yamlpnpm workspace (shared)
package.json with workspaces fieldnpm/yarn workspace (shared)
turbo.jsonTurborepo (shared)
Multiple subdirectories with separate package.json, no workspace configIsolated monorepo

Isolated monorepo (apps don't share code): set rootDirectory to the app's subdirectory (for example, /apps/api).

Shared monorepo (TypeScript workspaces, shared packages): do not set rootDirectory. Set custom build and start commands instead:

  • pnpm: pnpm --filter <package> build

  • npm: npm run build --workspace=packages/<package>

  • yarn: yarn workspace <package> build

  • Turborepo: turbo run build --filter=<package>

Scaffolding hints

When no code exists, minimal starting points for common types:

  • Static site: create index.html in the root directory.

  • Vite React: npm create vite@latest . -- --template react

  • Python FastAPI: create main.py with a FastAPI app and requirements.txt with fastapi and uvicorn.

  • Go: create main.go with an HTTP server that reads PORT from the environment.

Workspaces

Workspaces scope billing and team access. Most users have one personal workspace and possibly team workspaces.

railway whoami --json              # lists workspace memberships

When creating projects, Railway uses the default workspace unless --workspace is specified.

Troubleshoot setup issues

  • CLI missing: install via brew install railway or bash <(curl -fsSL https://railway.com/install.sh)

  • Not authenticated: railway login

  • Project not found: verify with railway project list --json, check workspace context

  • Service not found: railway service list --json to list services in the current environment

  • Wrong workspace: inspect railway whoami --json, re-run with explicit --workspace

  • Permission denied: check workspace role, mutations require member or admin access

Validated against

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Declares allowed tools, Needs an MCP server, Needs network access, Needs a command-line tool, Needs Python, Needs Node.js

Security

What our scanner noticed· Medium risk

  • References to credential files
  • Instructions that use the network
  • Downloads piped into a shell
  • Scripts that your agent may run

This skill includes scripts that your agent may run. Read them before you use it.

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Attribution and licence

Published by
Cline
Publisher
Cline (Official)
Source
cline/skills · skills/use-railway · commit 2637846
Licence
Apache License 2.0 (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
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