Deploy services, inspect logs, manage environments, and control your Railway infrastructure with AI.
Use with AI AssistantsMCP
Connect Claude, Cursor, or any MCP-compatible client — then call tools directly
① Add This MCP Server
Paste into your AI client config — then all its tools are available instantly.
{
"mcpServers": {
"railway": {
"url": "https://mcp.aerostack.dev/s/aerostack/mcp-railway",
"headers": {
"Authorization": "Bearer YOUR_AEROSTACK_TOKEN"
}
}
}
}Replace YOUR_AEROSTACK_TOKEN with your API token from the dashboard.
② Call a Tool
Ask your AI assistant to call a specific tool, or send raw JSON-RPC:
Natural Language Prompt
“Use the _ping tool to verify railway credentials by calling a lightweight read endpoint. used internally by aerostack to validate credentials”
Using a Workspace?
Add this MCP to your Workspace — your team shares one token, secrets are stored securely, and every AI agent in the workspace can call it without per-user setup.
Manage Railway projects, services, deployments, and logs from your AI agents.
Railway is the developer-friendly cloud platform for deploying backends, databases, and services with zero infrastructure configuration. This MCP server connects your AI agents to the Railway API — letting them inspect projects, check deployment health, stream logs, review environment variables, and trigger redeploys, all from natural language without opening the Railway dashboard.
Live endpoint: https://mcp.aerostack.dev/s/aerostack/mcp-railway
| Tool | Description |
|---|---|
list_projects | List all Railway projects for the authenticated user |
get_project | Get project details including environments and services |
list_services | List services in a Railway project |
list_deployments | List recent deployments for a service (last 10) |
get_deployment_logs | Get logs for a specific deployment |
list_variables | List environment variables for a service in an environment |
redeploy_service | Trigger a redeploy of a service in an environment |
| Variable | Required | Description | How to Get |
|---|---|---|---|
RAILWAY_API_TOKEN | Yes | Railway API token for GraphQL API authentication | railway.com/account/tokens → Create Token → give it a name → copy the token |
RAILWAY_API_TOKEN under Project → SecretsOnce added, every AI agent in your workspace can call Railway tools automatically — no per-user setup needed.
"List all my Railway projects and show the status of the most recent deployment for each"
"Get the last 100 log lines for the api-service deployment that failed 20 minutes ago"
"Redeploy the worker service in the production environment on the my-app project"
curl -X POST https://mcp.aerostack.dev/s/aerostack/mcp-railway \
-H 'Content-Type: application/json' \
-H 'X-Mcp-Secret-RAILWAY-API-TOKEN: your-api-token' \
-d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"list_projects","arguments":{}}}'
MIT
Live Endpoint
https://mcp.aerostack.dev/s/aerostack/mcp-railway
Sub-50ms globally · Zero cold start
@aerostack
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The Railway MCP gives Claude 7 tools covering projects, services, deployments. Claude can read, create, update, and manage Railway data directly from a conversation.
Yes. The Railway MCP includes tools to list and retrieve projects from your Railway account. Claude can filter, sort, and summarize projects based on your instructions.
Yes. The Railway MCP uses the open Model Context Protocol standard, so it works in Claude, Cursor, Windsurf, and any other MCP-compatible AI tool. All 7 Railway tools are available everywhere you connect it — install once on Aerostack.
Yes. Aerostack hosts the Railway MCP with encrypted credential storage and per-account authentication. Your Railway credentials are never shared with Claude's conversation — they're used server-side only.