Vinkius

Railway MCP. Manage Cloud Ops via Conversation

The Railway MCP lets your AI agent manage cloud deployments and infrastructure settings through natural conversation. List projects, check service statuses across environments like staging or production, track deployment histories, audit persistent storage volumes, and adjust environment variables—all without opening a browser 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

Audit Project Structure

Retrieve a complete list of your cloud projects, including names and basic details.

Inspect Services and Environments

See all deployed services (web apps, databases) within a project and filter them by specific environments like development or staging.

Track Deployment Status

Get the deployment history for any service to check success/failure statuses and timestamps.

Manage Config Variables

Check what environment variables exist or set new values for a specific service in a given environment.

Review Custom Domains

List custom domains assigned to services and check their SSL certificate status to ensure public access is working.

Waiting for input…

AI Agent
Railway

What AI agents can do with Railway Alternative: 10 Tools for Ops Management

These tools let your agent perform every essential operation on your cloud infrastructure, from listing projects to managing persistent storage.

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

Delete Variable

Permanently removes an environment variable from a service, which stops it from being used in future deployments.

List Deployments

Retrieves the full deployment history for a service, showing status, timestamps, and...

List Domains

Checks which custom domains are configured for a service and verifies their SSL...

List Environments

Lists the operational environments (like production or staging) configured within a...

Get Project

Retrieves detailed information about a single specific Railway project using its ID.

List Projects

Lists every cloud project associated with your account, giving you the starting point for all operations.

List Services

Shows all deployable units, such as web apps and databases, for a specified environment in a project.

Set Variable

Sets an environment variable value that will be available to all deployments of a...

List Variables

Lists environment variables for a service, indicating their scope (service...

Get Viewer

Use this to verify which account the API token belongs to. Get current...

List Volumes

Lists persistent storage volumes, showing their size and the services they are...

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 Pain of Dashboard Overload

Today, updating a simple variable or checking if a domain is live means logging into the Railway dashboard. You click on the project, then select the environment, navigate to 'Variables' just to check a value, and finally open another tab to view deployment logs. It’s a frustrating cycle of clicking through multiple menus.

With this MCP, you don't touch the browser. You simply ask your agent: 'What is the SSL status for my main API domain?' or 'Show me the latest build failure details.' The answer comes back in plain text, right where you are working.

Getting full operational visibility with Railway MCP

Before this, auditing a project's state meant running multiple commands—one for services, one for volumes, and another to list all environments. It was slow, manual, and error-prone.

Now, you ask the agent to 'Audit the whole API stack.' The system combines `list_services`, checks associated persistent storage via `list_volumes`, and validates deployment statuses in a single conversational response. You get full visibility instantly.

What Railway MCP does for your AI

Managing multi-service applications often means clicking through half a dozen tabs in the web console just to find one status update. This MCP changes that. It connects your AI agent directly to your Railway account, letting you handle complex cloud operations using plain chat. Need to know if production variables are set correctly? Ask.

Want to see why the last deployment failed? Just ask for the history. Your agent acts like a dedicated ops engineer, pulling data on everything from project details and service configurations to persistent storage volumes. Because this MCP is part of Vinkius's massive catalog, you connect once to your preferred AI client (like Cursor or Claude) and gain access to all your infrastructure tools in one place.

It gives you full control over your deployments right inside your existing workflow.

Built · Hosted · Managed by Vinkius Railway MCP - Manage Cloud Deployments with AI
Server ID 019d8474-6282-712f-bff9-e3bd0a47f2d9
Vinkius Inspector
Compliance Grade A+
Score 100/100
Vinkius Inspector Badge — Score 100/100

Frequently asked questions about Railway MCP

How do I use the list_projects tool with Railway MCP? +

You simply ask your agent to 'List all my Railway projects.' The system uses list_projects and returns a clean list of every project name, allowing you to select the right one for subsequent actions.

Does Railway MCP support environment variable deletion? +

Yes. If you need to remove an old or deprecated key, your agent can run delete_variable after confirming the service ID, environment ID, and variable name with you.

Can I check deployment status using list_deployments? +

Absolutely. By running list_deployments, your agent gives you a clear history of every attempt, showing success or failure statuses and when they occurred for the specific service.

What is the difference between listing services and list_environments? +

Use list_projects first to see all your projects. Then you use list_environments on a project to narrow down to 'staging' or 'production,' before finally running list_services for that specific environment.

Does Railway MCP show me which services are using volumes? +

Yes. Running the list_volumes tool shows you every persistent volume, and crucially, it links each volume ID to the specific service that is relying on that data.