Vinkius

Railway MCP. Control your entire cloud stack from conversation.

Railway MCP connects your AI agent directly to your live cloud infrastructure. Use it to manage projects, trigger deployments, restart services, and pull environment variables—all from your chat terminal without needing to open a web dashboard.

Railway MCP is compatible with Claude Claude
Railway MCP is compatible with ChatGPT ChatGPT
Railway MCP is compatible with Cursor Cursor
Railway MCP is compatible with Gemini Gemini
Railway MCP is compatible with Windsurf Windsurf
Railway MCP is compatible with VS Code VS Code
Railway MCP is compatible with JetBrains JetBrains
Railway MCP is compatible with Vercel Vercel
See Vinkius in Action

Give Claude and any AI agent real-world access

Manage Project Lifecycles

Create or retrieve details for specific cloud projects across your account.

Review Build Status and History

View a project's full deployment history, checking build statuses and rollout logs to ensure stability.

Troubleshoot Live Services

Get the current runtime configuration for services or restart an unhealthy container instance on demand.

Configure Environment Variables

Securely read, update, or sync sensitive environment keys across different service instances.

Initiate Code Deployments

Force a new deployment run for any connected service immediately after writing code.

Waiting for input…

AI Agent
Railway

What AI agents can do with Railway: 10 Tools for DevOps Operations

These ten tools give you programmatic control over every aspect of your Railway infrastructure—from creating new projects to managing runtime variables.

Make your AI actually useful.

Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.

Start using Railway MCP

Create Project

Creates a brand new cloud project within your Railway account.

Delete Project

Permanently removes an entire cloud project. Be careful; this action cannot be...

Get Project

Retrieves detailed information about a single, specific cloud project.

Get Service Instances

Fetches the current runtime configuration and details for an operational service.

List Deployments

Displays a list of all past and present deployments for a given project...

List Projects

Retrieves a comprehensive list of every Railway project your token has access to.

List Variables

Lists all current environment variables associated with a service, helping you check configuration keys.

Restart Service

Forcibly restarts a running service instance when it's behaving poorly or needs a...

Trigger Deploy

Initiates and queues up an entirely new deployment run for the specified service.

Whoami

Retrieves your personal profile information associated with the Railway API token.

Security and governance baked right in.

Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.

Railway MCP is compatible with Claude

Claude AI

1

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.

2

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.

3

Start a conversation

Open a new chat. The Railway integration is available immediately — no restart needed.

Choose How to Get Started

Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.

Build Your Own

Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.

  • Import from OpenAPI, Swagger, or YAML specs
  • Create Agent Skills with progressive disclosure
  • Deploy to edge with MCPFusion framework
  • Built in DLP, auth, and compliance on each call
  • Real time usage dashboard and cost metering
  • Publish to catalog or keep private
Start building

Make Your AI Do More

Start with Railway, then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.

  • Use this MCP plus 5,200+ others, all in one place
  • Add new capabilities to your AI anytime you want
  • Connections are secured and governed automatically
  • Track usage and costs across all your servers
  • Works with Claude, ChatGPT, Cursor, and more
  • New servers added to the catalog weekly
Railway MCP server cover

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Railway. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

VINKIUS CLOUD

Cloud Hosted

Managed infra

V8 Isolated

Sandboxed per request

Zero-Trust Proxy

No stored credentials

DLP Enforced

Policy on each call

GDPR Compliant

EU data residency

Token Compression

~60% cost reduction

Your data is protected. See how we built it.

The Operational Dashboard Overload

Today, keeping track of a deployment can be a nightmare. You have to open the cloud dashboard, navigate through project settings, click into service logs, and then check the deployment history page. It's a cycle of tabs, clicks, and copy-pasting status codes just to confirm if your code made it live.

With this MCP, that process vanishes. You simply ask your agent to list_deployments for the target service. The AI pulls all the necessary status information—build success, rollout logs, current environment details—and hands it back in plain language. It’s instant confirmation.

Project and Service Management with Railway MCP

The most tedious parts are the initial setup checks. Do you need to know what projects exist? You have to go to a list view. Is a service running properly? You're stuck checking the 'Instance Details'. And if it's broken, restarting requires going back and forth between menus.

Now, your agent handles all those manual steps. With tools like get_project or list_projects, you can audit your entire setup from one chat window. It’s not just reading; it’s controlling the state of your whole cloud stack.

What Railway MCP does for your AI

You can run core DevOps tasks right through your agent's conversational interface. Instead of opening multiple browser tabs or running complex CLI commands every time you need an update, your AI client handles the plumbing. You can ask it to list all projects available on your account or pull up a service’s runtime config instantly.

Need to verify if a recent code push succeeded? Just ask for deployment history and get the status back. If a container is acting up, triggering a restart is as simple as asking. This level of deep access lets you manage everything from project creation to sensitive configuration variables without ever leaving your chat window.

It's exactly what Vinkius delivers when it connects you to powerful services like Railway.

Built · Hosted · Managed by Vinkius Railway MCP - Manage Cloud Deployments & Services
Server ID 019d75fc-5c1f-7056-9bd5-1a8a44204e9c
Vinkius Inspector
Compliance Grade A+
Score 100/100
Vinkius Inspector Badge — Score 100/100

Frequently asked questions about Railway MCP

How do I use Railway MCP to see all my projects? +

You run the list_projects tool. This tells you every project linked to your account, which is a great first step before working on any single service.

Can I restart a service using the Railway MCP? If so, how? +

Yes, use the restart_service tool. Just provide the name of the running service instance, and the agent handles cycling its containers for you.

What if my latest deployment failed? Should I use list_deployments? +

Absolutely. Use list_deployments. This tool gives you a full timeline of build attempts and provides key details about where the rollout stopped, helping pinpoint the failure point.

Does Railway MCP let me change environment variables? +

Yes, it allows management via list_variables. You can check what values are currently set for a service instance before making any changes.

Is the delete_project action irreversible with the Railway MCP? +

The listing specifies that delete_project is an irreversible action, so always confirm you're deleting the correct project before running it.