Railway logo

Railway

Organization
railwayapp

Official Railway MCP Server for interacting with your Railway account

Publisherrailwayapp
Repositoryrailway-mcp-server
LanguageJavaScript
Forks
47
Stars
191
Available tools
14
Transport typestdio
Categories
LicenseMIT
Links
  • Connect tools to AI workflows

    Railway exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 14 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    191 stars and 47 forks from the linked repository.

@railway/mcp-server is deprecated

Railway MCP is now bundled into the Railway CLI.

This npm package no longer contains the standalone TypeScript MCP server. It is a compatibility shim that launches:

bash
railway mcp

Migration

Install or upgrade the Railway CLI:

bash
bash <(curl -fsSL https://railway.com/install.sh)

Then configure supported MCP clients:

bash
railway mcp install

To configure the hosted MCP server instead of the local stdio server:

bash
railway mcp install --remote

You can also configure a local MCP client directly with:

json
{
  "mcpServers": {
    "railway": {
      "command": "railway",
      "args": ["mcp"]
    }
  }
}

Remove old client entries that run:

bash
npx -y @railway/mcp-server

Compatibility

For existing configs that still invoke @railway/mcp-server, this package delegates to railway mcp.

If the Railway CLI is missing, the package exits with migration instructions.

Docs

See the Railway CLI MCP docs: https://docs.railway.com/cli/mcp

Installation

TypingMind
Prerequisites:

Node.js 18+

{
  "mcpServers": {
    "railway-mcp-server": {
      "command": "npx",
      "args": [
        "-y",
        "@railway/mcp-server"
      ]
    }
  }
}

Available Tools

  • check-railway-status

    Check whether the Railway CLI is installed and if the user is logged in. This tool helps agents verify the Railway CLI setup before attempting to use other Railway tools.

  • create-environment

    Create a new Railway environment for the currently linked project. Optionally duplicate an existing environment and set service variables.

  • create-project-and-link

    Create a new Railway project and link it to the current directory

  • deploy-template

    Search and deploy Railway templates. This tool will search for templates using fuzzy search and automatically deploy the selected template to the current Railway project and environment.

  • deploy

    Upload and deploy from the current directory. Supports CI mode, environment, and service options.

  • generate-domain

    Generate a domain for the currently linked Railway project. If a domain already exists, it will return the existing domain URL. Optionally specify a service to generate the domain for.

  • get-logs

    Get build or deployment logs for the currently linked Railway project. This will only pull the latest successful deployment by default, so if you need to inspect a failed build, you'll need to supply a deployment ID. You can optionally specify a deployment ID, service, and environment. If no deployment ID is provided, it will get logs from the latest deployment. The 'lines' and 'filter' parameters require Railway CLI v4.9.0+. Use 'lines' to limit the number of log lines (disables streaming) and 'filter' to search logs by terms or attributes (e.g., '@level:error', 'user', '@level:warn AND rate limit'). For older CLI versions, these parameters will be ignored and logs will stream.

  • link-environment

    Link to a specific Railway environment. If no environment is specified, it will list available environments for selection.

  • link-service

    Link a service to the current Railway project. If no service is specified, it will list available services

  • list-deployments

    List deployments for a Railway service with IDs, statuses and other metadata. Requires Railway CLI v4.10.0+.

  • list-projects

    List all Railway projects for the currently logged in account

  • list-services

    List all services for the currently linked Railway project

  • list-variables

    Show variables for the active environment

  • set-variables

    Set environment variables for the active environment

Use Railway MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once Railway is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add Railway as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the Railway MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "railway": {
      "command": "npx",
      "args": [
        "-y",
        "@railway/mcp-server"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the Railway MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the Railway MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use Railway to help me with this task?
Railway
Sure. I read it.
Here is what I found using Railway.

Frequently asked questions

What is the Railway MCP server used for?

Railway is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use Railway MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use Railway with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use Railway MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With Railway connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect Railway MCP to TypingMind?

Railway runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does Railway MCP provide in TypingMind?

Railway exposes 14 MCP tools that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use Railway MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If Railway requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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