Manage Railway infrastructure with MCP clients deploy services and monitor via natural language
The Railway MCP (Model Context Protocol) Server serves as an essential bridge between advanced AI tools and the Railway.app platform for modern cloud infrastructure management. Developed to empower developers and operations teams, it enables seamless interaction between various applications such as Claude Desktop, Cursor, Cline, Windsurf, and other Model Context Protocol clients through the standardized MCP protocol.
The key capabilities of this server include project, service, deployment, variable, and database management functionalities—all integrated effortlessly via natural language queries. Integration with Railway.app allows users to create, manage, and deploy services, monitor variables, and keep track of deployments, providing a unified interface for AI-powered tooling.
The Railway MCP Server supports robust features aligning closely with the Model Context Protocol standards:
Implementing the Model Context Protocol, the Railway MCP Server ensures cross-client compatibility by adhering strictly to established standards. The architecture is designed to streamline interactions between AI applications like Claude Desktop, Continue, Cursor, and others. Below are two Mermaid diagrams representing key aspects of its architecture:
graph TD
A[AI Application] -->|MCP Client| B[MCP Protocol]
B --> C[Railway MCP Server]
C --> D[Railway.app API]
style A fill:#e1f5fe
style C fill:#f3e5f5
style D fill:#e8f5e8
This diagram illustrates the protocol flow, showcasing how an AI application communicates through an MCP client to interact with the Railway MCP Server and ultimately perform actions on the Railway.app infrastructure.
graph TD
A[UI Input] --> B[MCP Client]
B --> C[MCP Protocol]
C --> D[Railway MCP Server]
D --> E[Railway.app API]
E --> F[API Response]
F --> G[Output UI Update]
style A fill:#e1f5fe
style C fill:#f3e5f5
style D fill:#f9d4a7
style E fill:#e8f5e8
style F fill:#d4f0fa
This diagram represents the data architecture, detailing how user inputs are processed through MCP clients to trigger internal server logic and API calls.
To get started with the Railway MCP Server, follow these steps:
Prerequisites:
This server works seamlessly with various MCP clients including:
For a streamlined installation experience, we recommend using Smithery.
To install the Railway MCP Server with Claude Desktop:
npx -y @smithery/cli install @jason-tan-swe/railway-mcp --client claude
For Cursor, run this command after setting your API token:
npx -y @smithery/cli@latest run @jason-tan-swe/railway-mcp --config "{\"railwayApiToken\":\"token\"}"
API_KEY
environment variable with your API token.npx @modelcontextprotocol/client-cursor --server-url https://railway-mcp.example.com --api-key "your-api-key"
For custom installations, ensure you set up your configuration file to resemble this sample:
{
"mcpServers": {
"[server-name]": {
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-[name]"],
"env": {
"API_KEY": "your-api-key"
}
}
}
}
MCP Client | Resources | Tools | Prompts | Status |
---|---|---|---|---|
Claude Desktop | ✅ | ✅ | ✅ | Full Support |
Continue | ✅ | ✅ | ✅ | Full Support |
Cursor | ❌ | ✅ | ❌ | Tools Only |
The integration matrix highlights the thorough compatibility and advanced support available for key AI tools.
Feature | Claude Desktop | Continue | Cursor | Cline | Windsurf |
---|---|---|---|---|---|
Authentication | ✅ | ✅ | ❌ | ❌ | ❌ |
Project Management | ✅ | ✅ | ✕ | ✕ | ✕ |
Service Management | ✅ | ✅ | ❌ | ✕ | ✕ |
Variable Management | ✅ | ✅ | ✕ | ✕ | ✕ |
Deployment Management | ✅ | ✅ | ❌ | ✕ | ✕ |
This matrix offers a detailed breakdown of the server's compatibility with various MCP clients.
To set up environmental configurations, use a JSON-like structure for setting key parameters. An example snippet follows:
{
"mcpServers": {
"railway-mcp-server": {
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-railway"],
"env": {
"RAILWAY_API_KEY": "your-api-key"
}
}
}
}
Q: How do I ensure seamless integration with MCP clients?
Q: Can I integrate this server with other AI applications that aren't supported by default?
Q: Is there an API documentation available for advanced users?
Q: How do I manage sensitive information like API keys within my applications?
Q: Can this server be integrated into existing CI/CD workflows?
To contribute to improving functionalities and addressing issues within the Railway MCP Server:
npm install
in the repository directory.npm test
to check code quality and integration.Join our community forums and chat groups for real-time support and collaboration:
By leveraging the Railway MCP Server, developers can significantly enhance their AI workflows, making management and deployment processes smoother and more straightforward. This seamless integration aligns closely with the Model Context Protocol's vision of universality in application interactivity.
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