# Railway MCP

```json
{
  "name": "Railway MCP",
  "slug": "railway_mcp",
  "url": "https://composio.dev/toolkits/railway_mcp",
  "markdown_url": "https://composio.dev/toolkits/railway_mcp.md",
  "logo_url": "https://logos.composio.dev/api/railway_mcp",
  "categories": [
    "developer tools & devops"
  ],
  "is_composio_managed": false,
  "updated_at": "2026-08-25T05:33:47.803Z"
}
```

![Railway MCP logo](https://logos.composio.dev/api/railway_mcp)

## Description

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.

## Summary

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.

## Categories

- developer tools & devops

## Toolkit Details

- Tools: 26

## Images

- Logo: https://logos.composio.dev/api/railway_mcp

## Authentication

- **Oauth2**
  - Type: `oauth2`
  - Description: Oauth2 authentication for Railway MCP.
  - Setup:
    - Configure Oauth2 credentials for Railway MCP.
    - Use the credentials when creating an auth config in Composio.

## Suggested Prompts

- Deploy latest commit to production service
- List all services and environment variables
- Create staging environment and deploy service

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `RAILWAY_MCP_ACCEPT_DEPLOY` | Accept-deploy | DESTRUCTIVE: Commits all staged changes in a Railway environment and triggers a deploy. Only use this when the user has explicitly confirmed they want to deploy. |
| `RAILWAY_MCP_CREATE_DEPLOYMENT` | Create-deployment | Create a new service from a GitHub repository and trigger its first deployment. The repo must be one the authenticated user has connected via GitHub. Returns the new service; use get-status or list-deployments to follow the deploy. Before calling this tool you MUST have a GitHub repo to deploy. If the user has not provided one, do not guess — first ask them which GitHub repo to deploy (in 'owner/name' form). If they don't have a repo yet, offer to help create one: if you have tools available to create a GitHub repository (e.g. a GitHub MCP server or `gh` CLI), offer to scaffold and push one for them; otherwise point them to create a repo on GitHub and share its 'owner/name'. Only call this tool once a concrete repo has been confirmed. |
| `RAILWAY_MCP_CREATE_PROJECT` | Create-project | Create a new Railway project |
| `RAILWAY_MCP_CREATE_SERVICE` | Create-service | Create a new service in a project from a Docker image, or an empty service to configure later (e.g. before setting variables and attaching a source). To create a service from a GitHub repository, use create-deployment instead. |
| `RAILWAY_MCP_DELETE_FEATURE_FLAG` | Delete-feature-flag | Delete a project-scoped feature flag. Workspace-scoped flags cannot be deleted from project context. |
| `RAILWAY_MCP_FETCH_DOCS` | Fetch-docs | Fetch the full markdown content of a Railway documentation page by URL or slug (e.g. 'https://docs.railway.com/quick-start' or 'reference/variables'). Use search-docs first to find the right page. |
| `RAILWAY_MCP_GENERATE_DOMAIN` | Generate-domain | Expose a service publicly. Without `domain`, generates a Railway *.up.railway.app service domain (if the service already has domains, they are returned instead of creating another). With `domain`, attaches a custom domain you own and returns the DNS records the user must create for it to verify. If environmentId is omitted, the production environment is used. |
| `RAILWAY_MCP_GET_FEATURE_FLAG` | Get-feature-flag | Get a Railway feature flag (Signal) by name for a project or its parent workspace scope. |
| `RAILWAY_MCP_GET_LOGS` | Get-logs | Get logs from Railway for a deployment — covers deploy (runtime), build, and http (proxy request) contexts. Pass a specific deploymentId, or pass serviceId + environmentId to resolve the latest deployment. Use `types` to choose which streams to return (default: ['deploy']). |
| `RAILWAY_MCP_GET_SERVICE_CONFIG` | 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. Variable names are listed but values are not included — use list-variables for values. If environmentId is omitted, the production environment is used. |
| `RAILWAY_MCP_GET_SERVICE_METRICS` | Get-service-metrics | Get resource usage metrics (CPU, memory, disk, network) for a service, summarized as current/average/min/max over a time window. Defaults to CPU_USAGE and MEMORY_USAGE_GB over the last hour. If environmentId is omitted, the production environment is used. |
| `RAILWAY_MCP_GET_STATUS` | Get-status | Get the deployment status of a Railway project environment. Returns project + environment metadata and, for each service in the environment, its latest deployment status, replica count, and cron schedule. If environmentId is omitted, the project's `production` environment is used when present, otherwise the oldest environment. |
| `RAILWAY_MCP_LIST_DEPLOYMENTS` | List-deployments | List recent deployments for a Railway project, optionally filtered by environment, service, or status. Returns the most recent first. |
| `RAILWAY_MCP_LIST_DOMAINS` | List-domains | List all domains (Railway-generated service domains and custom domains) for a service in an environment. If environmentId is omitted, the production environment is used. |
| `RAILWAY_MCP_LIST_FEATURE_FLAGS` | List-feature-flags | List Railway feature flags (Signals) for a project and optionally the parent workspace. Project flags are editable with admin access; workspace flags are read-only from project context. |
| `RAILWAY_MCP_LIST_PROJECTS` | List-projects | List all Railway projects accessible to the authenticated user |
| `RAILWAY_MCP_LIST_SERVICES` | List-services | List all services and environments in a Railway project |
| `RAILWAY_MCP_LIST_VARIABLES` | List-variables | List all environment variables for a service, fully rendered (reference variables like ${{Postgres.DATABASE_URL}} are resolved). With a Railway session or API token, values are returned in plaintext and may contain secrets. Connected OAuth apps receive variable names only. If environmentId is omitted, the production environment is used. |
| `RAILWAY_MCP_LIST_WORKSPACES` | List-workspaces | List the Railway workspaces the current user belongs to. Use a workspace ID with create-project to choose where a project is created. |
| `RAILWAY_MCP_RAILWAY_AGENT` | Railway-agent | Send a message to Railway's AI agent for complex infrastructure operations. The agent can inspect services, diagnose issues, and take actions on your behalf. |
| `RAILWAY_MCP_REDEPLOY` | Redeploy | Re-run the most recent deployment of a service in a given environment, reusing that deployment's existing build. Only works on a service that has already deployed in that environment — check with list-deployments if you are unsure. This does NOT give a service its first deployment: if it has never deployed, nothing here can deploy it, and create-deployment would build a separate new service from a GitHub repo rather than deploying this one. |
| `RAILWAY_MCP_SEARCH_DOCS` | Search-docs | Search the Railway documentation (docs.railway.com) for features, configuration, guides, and tutorials. Returns matching sections with URLs — use fetch-docs to read a full page. |
| `RAILWAY_MCP_SET_FEATURE_FLAG` | Set-feature-flag | Create a project-scoped feature flag or update its default value. Use list-feature-flags and get-feature-flag to inspect existing flags first. |
| `RAILWAY_MCP_SET_VARIABLES` | Set-variables | Set one or more environment variables on a service (or environment-wide shared variables when serviceId is omitted). Existing variables with the same name are overwritten; others are left unchanged. Reference syntax like ${{Postgres.DATABASE_URL}} is supported. Affected services are redeployed unless skipDeploys is true. |
| `RAILWAY_MCP_UPDATE_SERVICE` | 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. Only the fields you pass are changed. Changes apply on the service's next deployment (use redeploy to apply immediately). Scaling (replicas/regions) and source changes are not handled by this tool. |
| `RAILWAY_MCP_WHOAMI` | Whoami | Get the current authenticated Railway user's profile information |

## Supported Triggers

None listed.

## Installation and MCP Setup

### Path 1: SDK Installation

#### Path 1, Step 1: Install Composio

Install the Composio SDK
```python
pip install composio_openai
```

```typescript
npm install @composio/openai
```

#### Path 1, Step 2: Initialize Composio and Create Tool Router Session

Import and initialize Composio client, then create a Tool Router session
```python
from openai import OpenAI
from composio import Composio
from composio_openai import OpenAIResponsesProvider

composio = Composio(provider=OpenAIResponsesProvider())
openai = OpenAI()
session = composio.create(user_id='your-user-id')
```

```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');
```

#### Path 1, Step 3: Execute Railway MCP Tools via Tool Router with Your Agent

Get tools from Tool Router session and execute Railway MCP actions with your Agent
```python
tools = session.tools
response = openai.responses.create(
  model='gpt-4.1',
  tools=tools,
  input=[{
    'role': 'user',
    'content': 'Deploy latest commit to production service'
  }]
)
result = composio.provider.handle_tool_calls(
  response=response,
  user_id='your-user-id'
)
print(result)
```

```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);
```

### Path 2: MCP Server Setup

#### Path 2, Step 1: Install Composio

Install the Composio SDK for Python or TypeScript
```python
pip install composio claude-agent-sdk
```

```typescript
npm install @composio/core ai @ai-sdk/openai @ai-sdk/mcp
```

#### Path 2, Step 2: Initialize Client and Create Tool Router Session

Import and initialize the Composio client, then create a Tool Router session for Railway MCP
```python
from composio import Composio
from claude_agent_sdk import ClaudeSDKClient, ClaudeAgentOptions

composio = Composio(api_key='your-composio-api-key')
session = composio.create(user_id='your-user-id')
url = session.mcp.url
```

```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}`);
```

#### Path 2, Step 3: Connect to AI Agent

Use the MCP server with your AI agent (Anthropic Claude or Mastra)
```python
import asyncio

options = ClaudeAgentOptions(
    permission_mode='bypassPermissions',
    mcp_servers={
        'tool_router': {
            'type': 'http',
            'url': url,
            'headers': {
                'x-api-key': 'your-composio-api-key'
            }
        }
    },
    system_prompt='You are a helpful assistant with access to Railway MCP tools.',
    max_turns=10
)

async def main():
    async with ClaudeSDKClient(options=options) as client:
        await client.query('Deploy latest commit to production service')
        async for message in client.receive_response():
            if hasattr(message, 'content'):
                for block in message.content:
                    if hasattr(block, 'text'):
                        print(block.text)

asyncio.run(main())
```

```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}`);
```

## Why Use Composio?

### 1. 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

### 2. 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

### 3. 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

### 4. 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

## Use Railway MCP with any AI Agent Framework

Choose a framework you want to connect Railway MCP with:

- [ChatGPT Work](https://composio.dev/toolkits/railway_mcp/framework/chatgpt)
- [Claude Cowork](https://composio.dev/toolkits/railway_mcp/framework/claude-cowork)
- [Hermes](https://composio.dev/toolkits/railway_mcp/framework/hermes-agent)

## Related Toolkits

- [Supabase](https://composio.dev/toolkits/supabase) - Supabase is an open-source backend platform offering scalable Postgres databases, authentication, storage, and real-time APIs. It lets developers build modern apps without managing infrastructure.
- [Codeinterpreter](https://composio.dev/toolkits/codeinterpreter) - Codeinterpreter is a Python-based coding environment with built-in data analysis and visualization. It lets you instantly run scripts, plot results, and prototype solutions inside supported platforms.
- [GitHub](https://composio.dev/toolkits/github) - GitHub is a code hosting platform for version control and collaborative software development. It streamlines project management, code review, and team workflows in one place.
- [1password](https://composio.dev/toolkits/_1password) - 1Password is a password manager and digital vault for storing logins, secrets, notes, and secure documents. It helps individuals and teams protect credentials, share access safely, and reduce password risk.
- [Ably](https://composio.dev/toolkits/ably) - Ably is a real-time messaging platform for live chat and data sync in modern apps. It offers global scale and rock-solid reliability for seamless, instant experiences.
- [Abuselpdb](https://composio.dev/toolkits/abuselpdb) - Abuselpdb is a central database for reporting and checking IPs linked to malicious online activity. Use it to quickly identify and report suspicious or abusive IP addresses.
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- [Anchor browser](https://composio.dev/toolkits/anchor_browser) - Anchor browser is a developer platform for AI-powered web automation. It transforms complex browser actions into easy API endpoints for streamlined web interaction.
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- [Appveyor](https://composio.dev/toolkits/appveyor) - AppVeyor is a cloud-based continuous integration service for building, testing, and deploying applications. It helps developers automate and streamline their software delivery pipelines.
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- [AWS Marketplace MCP](https://composio.dev/toolkits/aws_marketplace_mcp) - AWS Marketplace MCP provides MCP access to AWS Marketplace's cloud software, data, and services catalog. Use it to discover, compare, and evaluate 30K+ AWS Marketplace listings faster.
- [Azure Monitor Activity Log](https://composio.dev/toolkits/azure_monitor_activity_log) - Azure Monitor Activity Log is Azure's service that records management and control-plane events for a subscription. Use it to audit changes, troubleshoot issues, and track resource operations across your Azure resources.
- [Backendless](https://composio.dev/toolkits/backendless) - Backendless is a backend-as-a-service platform for mobile and web apps, offering database, file storage, user authentication, and APIs. It helps developers ship scalable applications faster without managing server infrastructure.
- [Baserow](https://composio.dev/toolkits/baserow) - Baserow is an open-source no-code database platform for building collaborative data apps. It makes it easy for teams to organize data and automate workflows without writing code.
- [Bench](https://composio.dev/toolkits/bench) - Bench is a benchmarking tool for automated performance measurement and analysis. It helps you quickly evaluate, compare, and track your systems or workflows.

## Frequently Asked Questions

### Do I need my own developer credentials to use Railway MCP with Composio?

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

### Can I use multiple toolkits together?

Yes! Composio's Tool Router enables agents to use multiple toolkits. [Learn more](https://docs.composio.dev/tool-router/overview).

### Is Composio secure?

Composio is SOC 2 and ISO 27001 compliant with all data encrypted in transit and at rest. [Learn more](https://trust.composio.dev).

### What if the API changes?

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

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)