Infrastructure platform
## Railway MCP Server: Cloud Deployment Platform The **Railway MCP Server** integrates Railway cloud platform into Google Antigravity, enabling seamless deployment, monitoring, and management of applications with automatic builds, databases, and environment management. ### Why Railway MCP? - **Instant Deploys**: Push code and get a running application in seconds with automatic builds - **Database Provisioning**: One-click PostgreSQL, MySQL, Redis, and MongoDB instances - **Environment Management**: Isolated environments for development, staging, and production - **Usage Monitoring**: Real-time resource usage and cost tracking - **GitHub Integration**: Automatic deployments on push with preview environments ### Key Features #### 1. Project Deployment ```python # Deploy from GitHub deployment = await mcp.deploy( project_id="project_123", service_name="web", source={ "repo": "org/myapp", "branch": "main" } ) print(f"Deployment: {deployment['id']}") print(f"URL: {deployment['url']}") # Check deployment status status = await mcp.get_deployment(deployment_id=deployment["id"]) print(f"Status: {status['status']}") ``` #### 2. Service Management ```python # List services in project services = await mcp.list_services(project_id="project_123") for service in services: print(f"Service: {service['name']} - {service['status']}") # Scale a service await mcp.update_service( project_id="project_123", service_id="service_456", replicas=3, memory_mb=512 ) # View service logs async for log in mcp.stream_logs(service_id="service_456"): print(log) ``` #### 3. Database Operations ```python # Create a PostgreSQL database db = await mcp.create_database( project_id="project_123", plugin="postgresql", name="myapp-db" ) print(f"Connection URL: {db['connection_url']}") # List databases databases = await mcp.list_databases(project_id="project_123") for db in databases: print(f"Database: {db['name']} ({db['plugin']})") ``` #### 4. Environment Variables ```python # Set environment variables await mcp.set_variables( project_id="project_123", service_id="service_456", variables={ "NODE_ENV": "production", "API_KEY": "secret-key" } ) # Get variables vars = await mcp.get_variables( project_id="project_123", service_id="service_456" ) ``` ### Configuration ```json { "mcpServers": { "railway": { "command": "npx", "args": ["-y", "@anthropic/mcp-railway"], "env": { "RAILWAY_API_TOKEN": "your-api-token", "RAILWAY_PROJECT_ID": "your-default-project" } } } } ``` ### Use Cases **Rapid Prototyping**: Deploy proof-of-concept applications quickly with automatic HTTPS, domains, and database provisioning. **Preview Environments**: Create isolated preview environments for each pull request with automatic cleanup. **Microservices**: Deploy and manage multiple interconnected services with shared networking and environment variables. **Database Management**: Provision and manage databases alongside applications with automatic connection string injection. The Railway MCP enables streamlined cloud deployment directly within your Google Antigravity development environment.
{
"mcpServers": {
"railway": {
"mcpServers": {
"railway": {
"env": {
"RAILWAY_TOKEN": "your-token"
},
"args": [
"-y",
"railway-mcp-server"
],
"command": "npx"
}
}
}
}
}