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Railway MCP for AI Agents

Securely connect your AI agents and chatbots (Claude, ChatGPT, Cursor, etc) with Railway MCP or direct API to create projects and services, inspect environments and variables, trigger deployments, and manage deployment rollbacks through natural language.

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Railway MCP is Railway's hosted MCP server for managing projects, services, environments, variables, and deployments. Use it to automate deployments, inspect environments, and manage runtime configuration from AI agents.

26 Tools

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Type what you want done — sign in and watch it run live in the Tool Router playground.

TOOL ROUTER PLAYGROUND
Railway MCP
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TOOLS

Supported Tools

Every Railway MCP action and event your agent gets out of the box.

Accept-deploy

DESTRUCTIVE: Commits all staged changes in a Railway environment and triggers a deploy.

Create-deployment

Create a new service from a GitHub repository and trigger its first deployment.

Create-project

Create a new Railway project

Create-service

Create a new service in a project from a Docker image, or an empty service to configure later (e.

Delete-feature-flag

Delete a project-scoped feature flag.

Fetch-docs

Fetch the full markdown content of a Railway documentation page by URL or slug (e.

Generate-domain

Expose a service publicly.

Get-feature-flag

Get a Railway feature flag (Signal) by name for a project or its parent workspace scope.

Get-logs

Get logs from Railway for a deployment — covers deploy (runtime), build, and http (proxy request) contexts.

Get-service-config

Get a service's configuration in an environment: source (repo/image), build settings, deploy settings (start command, healthcheck, replicas, cron, restart policy), networking, and volume mounts.

Get-service-metrics

Get resource usage metrics (CPU, memory, disk, network) for a service, summarized as current/average/min/max over a time window.

Get-status

Get the deployment status of a Railway project environment.

List-deployments

List recent deployments for a Railway project, optionally filtered by environment, service, or status.

List-domains

List all domains (Railway-generated service domains and custom domains) for a service in an environment.

List-feature-flags

List Railway feature flags (Signals) for a project and optionally the parent workspace.

List-projects

List all Railway projects accessible to the authenticated user

List-services

List all services and environments in a Railway project

List-variables

List all environment variables for a service, fully rendered (reference variables like ${{Postgres.

List-workspaces

List the Railway workspaces the current user belongs to.

Railway-agent

Send a message to Railway's AI agent for complex infrastructure operations.

Redeploy

Re-run the most recent deployment of a service in a given environment, reusing that deployment's existing build.

Search-docs

Search the Railway documentation (docs.

Set-feature-flag

Create a project-scoped feature flag or update its default value.

Set-variables

Set one or more environment variables on a service (or environment-wide shared variables when serviceId is omitted).

Update-service

Update a service's configuration: build/start/pre-deploy commands, healthcheck, sleep mode, root directory, cron schedule, Dockerfile path, restart policy, config file path, and watch patterns.

Whoami

Get the current authenticated Railway user's profile information

SETUP GUIDE

Connect Railway MCP Tool with your Agent

1

Install Composio

typescript
npm install @composio/core ai @ai-sdk/openai @ai-sdk/mcp
Install the Composio SDK for Python or TypeScript
2

Initialize Client and Create Tool Router Session

typescript
import { Composio } from '@composio/core';

const composio = new Composio({ apiKey: 'your-api-key' });
const session = await composio.create('your-user-id');
console.log(`Tool Router session created: ${session.mcp.url}`);
Import and initialize the Composio client, then create a Tool Router session for Railway MCP
3

Connect to AI Agent

typescript
import { openai } from '@ai-sdk/openai';
import { experimental_createMCPClient as createMCPClient } from '@ai-sdk/mcp';
import { generateText } from 'ai';

const client = await createMCPClient({
  transport: {
    type: 'http',
    url: session.mcp.url,
    headers: {
      'x-api-key': 'your-composio-api-key',
    },
  },
});

const tools = await client.tools();
const { text } = await generateText({
  model: openai('gpt-4o'),
  tools,
  messages: [{
    role: 'user',
    content: 'Deploy latest commit to production service'
  }],
  maxSteps: 5,
});

console.log(`Agent: ${text}`);
Use the MCP server with your AI agent (Anthropic Claude or Mastra)
SETUP GUIDE

Connect Railway MCP API Tool with your Agent

1

Install Composio

typescript
npm install @composio/openai
Install the Composio SDK
2

Initialize Composio and Create Tool Router Session

typescript
import OpenAI from 'openai';
import { Composio } from '@composio/core';
import { OpenAIResponsesProvider } from '@composio/openai';

const composio = new Composio({
  provider: new OpenAIResponsesProvider(),
});
const openai = new OpenAI({});
const session = await composio.create('your-user-id');
Import and initialize Composio client, then create a Tool Router session
3

Execute Railway MCP Tools via Tool Router with Your Agent

typescript
const tools = session.tools;
const response = await openai.responses.create({
  model: 'gpt-4.1',
  tools: tools,
  input: [{
    role: 'user',
    content: 'Deploy latest commit to production service'
  }],
});
const result = await composio.provider.handleToolCalls(
  'your-user-id',
  response.output
);
console.log(result);
Get tools from Tool Router session and execute Railway MCP actions with your Agent

Why Use Composio?

AI Native Railway MCP Integration

  • Supports both Railway MCP and direct API based integrations
  • Structured, LLM-friendly schemas for reliable tool execution
  • Rich coverage for reading, writing, and querying your Railway MCP data

Managed Auth

  • Built-in OAuth handling with automatic token refresh and rotation
  • Central place to manage, scope, and revoke Railway MCP access
  • Per user and per environment credentials instead of hard-coded keys

Agent Optimized Design

  • Tools are tuned using real error and success rates to improve reliability over time
  • Comprehensive execution logs so you always know what ran, when, and on whose behalf

Enterprise Grade Security

  • Fine-grained RBAC so you control which agents and users can access Railway MCP
  • Scoped, least privilege access to Railway MCP resources
  • Full audit trail of agent actions to support review and compliance
FRAMEWORKS

Use Railway MCP with any AI Agent Framework

Choose a Framework you want to connect Railway MCP with

ChatGPT Work logo

ChatGPT Work

Use Railway MCP with ChatGPT Work

Claude Cowork logo

Claude Cowork

Use Railway MCP with Claude Cowork

Hermes logo

Hermes

Use Railway MCP with Hermes

FAQ

Frequently asked questions

Yes, Railway MCP requires you to configure your own OAuth credentials. Once set up, Composio handles token storage, refresh, and lifecycle management for you.

Yes! Composio's Tool Router enables agents to use multiple toolkits. Learn more.

Composio is SOC 2 and ISO 27001 compliant with all data encrypted in transit and at rest. Learn more.

Composio maintains and updates all toolkit integrations automatically, so your agents always work with the latest API versions.

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Managed auth, hosted MCP servers, and every Railway MCP tool your agent needs.Free to start.

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