Railway MCP
Create, inspect, deploy, and manage Railway projects, services, environments, variables, and deployments through Railway's hosted MCP server.
Verdict
Common use cases
- Check deployment status during standups
- Pull service logs when debugging incidents
- Review environment variables before releases
- Monitor resource usage across staging environments
- Surface recent build failures for triage
Integration
- Vendor
- Railway MCP
- Category
- developer-tools
- Auth
- OAUTH2
- Composio slug
railway_mcp
Tools
Setup
Setup guide
- 11. Open your Switchy workspace and navigate to Settings > Integrations. 2. Find Railway MCP in the developer tools section and click Connect. 3. You'll redirect to Railway's OAuth consent screen — sign in with your Railway account. 4. Grant Switchy read access to your projects, services, deployments, and logs (Railway requests these scopes to surface deployment data). 5. After authorizing, you'll return to Switchy with a confirmation that Railway MCP is connected. 6. Open any Project in Switchy and type '@Railway show recent deployments' to test the connection. 7. If the MCP responds with deployment history, you're ready — if it errors, revisit Settings > Integrations to reconnect and verify scopes.
What teammates see: by default, memories from Railway MCP are scoped to the Project (PROJECT visibility) - you can mark any memory PRIVATE or share it ORG-wide.
Works well with
Top models
Compatibility data appears once enough Projects have used this MCP together with a given model.
How Switchy teams use it
Starter prompts
Deployment Health Check
@Railway list all deployments from the past hour and highlight any that failed or are still in progress
Log Search for Errors
@Railway search logs for the api-service in production for any errors containing 'timeout' in the last 30 minutes
Environment Variable Audit
@Railway show all environment variables for the web-service in the staging environment
Resource Usage Summary
@Railway summarize CPU and memory usage for all services in the production project over the last 24 hours
Recent Build Failures
@Railway list the last 5 failed builds across all projects and include the error message for each
Example outputs
Illustrative - representative of the model's voice and quality, not literal recordings.
@railway show me the deployment status and recent logs for my production API service
Railway reports your production API service (service-abc123) is currently running with 2 replicas. Latest deployment completed 14 minutes ago from commit 7a3f9e2. Recent logs show 47 successful requests in the past 5 minutes, average response time 120ms. No error spikes detected. Memory usage at 340MB per replica, well within your 512MB limit.
This read-heavy example assumes OAuth2 scope includes deployment and log access. Railway's log streaming is time-windowed — you'll see recent entries, not full history. Useful for quick health checks without leaving your workspace, though deep debugging still requires Railway's dashboard.
@railway scale my staging database service down to zero replicas until Monday morning
Scaled staging database service (postgres-staging-xyz) to 0 replicas. Service will stop accepting connections and incur no compute charges until manually restarted. Note: Railway doesn't support scheduled auto-restart — you'll need to manually scale back up Monday or use a separate cron job to trigger the API.
This write example demonstrates cost control for non-production environments. Scaling to zero is immediate but requires manual reversal. If your staging service has persistent volumes, data remains intact. Be cautious with production services — zero replicas means downtime.
@railway compare resource usage across all my services this week and suggest which ones could be downsized
Analyzed 6 services over the past 7 days. Three candidates for downsizing: worker-queue averaged 18% CPU and 210MB memory (provisioned for 1GB), background-jobs peaked at 35% CPU during nightly runs, and redis-cache consistently used under 40% of allocated memory. Your frontend and API services show healthy utilization near their limits. Downsizing the three underutilized services could reduce monthly spend by approximately 30%.
This synthesis example pairs Railway's metrics with AI reasoning to surface optimization opportunities. Accuracy depends on Railway exposing granular usage data via the MCP. Recommendations are directional — validate peak load patterns before making changes, especially for services with spiky traffic.
Use-case deep-dives
When Railway MCP saves time in daily sync meetings
A 5-person engineering team runs 15-minute standups where blockers surface fast. The Railway MCP lets anyone in the Switchy workspace check deployment status, read recent logs, or confirm environment variables without leaving the conversation thread. OAuth2 auth means each person connects their own Railway account once, then the team shares access to the same deployment context. This works when your team deploys 3-8 times a day and needs instant answers without opening Railway's dashboard. If your deploy cadence is weekly or slower, the overhead of connecting another MCP probably isn't worth it. For teams shipping continuously, this MCP turns 'let me check Railway and get back to you' into a 10-second inline answer.
Railway MCP as a first-response tool during outages
A startup's on-call rotation covers 3 engineers who need to diagnose production issues at 2am. The Railway MCP pulls deployment history, service health, and error logs into Switchy's shared context so the on-call engineer can brief the team without switching tabs. OAuth2 means each engineer authenticates once and the MCP respects their Railway permissions. This setup shines when your incident response is collaborative—multiple people jumping into a Switchy thread to debug together. If your on-call process is solo and you already live in Railway's UI during incidents, adding this MCP just duplicates your workflow. For teams that triage in Slack or similar tools and want Railway data in the same place, this MCP closes the context gap.
When Railway MCP bridges support and engineering handoffs
A 6-person team runs customer support and engineering in the same Switchy workspace. Support needs to confirm whether a bug fix deployed to staging before escalating a ticket. The Railway MCP lets support check staging status and recent deploys without pinging engineering or learning Railway's interface. OAuth2 keeps permissions intact—support sees only what Railway allows them to see. This works when your support team handles 20+ tickets a day and staging deploys happen multiple times daily. If your support volume is low or your team prefers a strict engineering-only deployment boundary, the MCP adds friction instead of removing it. For teams where support and engineering collaborate tightly on release validation, this MCP turns 'is the fix live?' into a self-service lookup.
Frequently asked
What does the Railway MCP do in Switchy?
The Railway MCP connects your Railway account to Switchy's AI workspace, letting your team query deployment status, environment variables, and project configurations without leaving the chat. It's useful for teams that want to check Railway infrastructure details or troubleshoot deploys during a conversation, rather than switching to the Railway dashboard.
Do I need admin access to connect Railway via OAuth?
You'll need a Railway account with read access to the projects you want to query. Railway's OAuth flow typically requests permissions to view your projects and deployments. If your team uses Railway's team workspaces, check that your role allows API access — some orgs restrict this to admins or developers.
Can the Railway MCP trigger new deployments or change environment variables?
That depends on which Railway API endpoints the MCP exposes as tools. Most read-only MCPs let you query deployment logs and project status but won't push code or modify configs. If you need to trigger deploys from Switchy, check the tool list once it's populated — or use Railway's CLI in a separate workflow.
Why use this instead of just opening the Railway dashboard?
The MCP keeps your team in one workspace. Instead of someone asking 'is staging down?' and three people tabbing to Railway, the AI fetches the answer inline. It's faster for quick checks during incident response or standups. For complex changes or visual debugging, you'll still want the dashboard.
Does connecting Railway count against my Switchy plan limits?
MCP connections don't consume seat limits — they're tied to the workspace, not individual users. However, if your team makes heavy use of Railway queries, those AI requests count toward your monthly message quota. One person connecting Railway via OAuth makes it available to everyone in the workspace.