Railway MCP Server for Windsurf 10 tools — connect in under 2 minutes
Windsurf brings agentic AI coding to a purpose-built IDE. Connect Railway through Vinkius and Cascade will auto-discover every tool. ask questions, generate code, and act on live data without leaving your editor.
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The modern way to manage MCP Servers — no config files, no terminal commands. Install Railway and 2,500+ MCP Servers from a single visual interface.




{
"mcpServers": {
"railway": {
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
}
}
}
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Railway MCP Server
Connect your Railway cloud infrastructure to an AI agent, streamlining operations directly from your chat terminal. By configuring this integration, the AI gains programmatic management over your active deployments and environments.
Windsurf's Cascade agent chains multiple Railway tool calls autonomously. query data, analyze results, and generate code in a single agentic session. Paste Vinkius Edge URL, reload, and all 10 tools are immediately available. Real-time tool feedback appears inline, so you see API responses directly in your editor.
What you can do
- Project Management — Create new projects or query existing ones to assess active cloud architectures without opening the web dashboard.
- Deployment Oversight — Review build statuses, trigger new deployments, and read rollout logs to ensure stable releases.
- Service Configuration — List, update, or restart operational services mapped within your Railway projects securely.
- Environment Variables — Manage sensitive configuration keys by securely pulling, updating, or syncing environment values across instances.
The Railway MCP Server exposes 10 tools through the Vinkius. Connect it to Windsurf in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Railway to Windsurf via MCP
Follow these steps to integrate the Railway MCP Server with Windsurf.
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
Add the server
Paste the JSON configuration above into mcp_config.json
Save and reload
Windsurf will detect the new server automatically
Start using Railway
Open Cascade and ask: "Using Railway, help me...". 10 tools available
Why Use Windsurf with the Railway MCP Server
Windsurf provides unique advantages when paired with Railway through the Model Context Protocol.
Windsurf's Cascade agent autonomously chains multiple tool calls in sequence, solving complex multi-step tasks without manual intervention
Purpose-built for agentic workflows. Cascade understands context across your entire codebase and integrates MCP tools natively
JSON-based configuration means zero code changes: paste a URL, reload, and all 10 tools are immediately available
Real-time tool feedback is displayed inline, so you see API responses directly in your editor without switching contexts
Railway + Windsurf Use Cases
Practical scenarios where Windsurf combined with the Railway MCP Server delivers measurable value.
Automated code generation: ask Cascade to fetch data from Railway and generate models, types, or handlers based on real API responses
Live debugging: query Railway tools mid-session to inspect production data while debugging without leaving the editor
Documentation generation: pull schema information from Railway and have Cascade generate comprehensive API docs automatically
Rapid prototyping: combine Railway data with Cascade's code generation to scaffold entire features in minutes
Railway MCP Tools for Windsurf (10)
These 10 tools become available when you connect Railway to Windsurf via MCP:
create_project
Creates a new Railway project
delete_project
This action is irreversible. Deletes a Railway project
get_project
Retrieves details for a specific Railway project
get_service_instances
Retrieves runtime configuration for a service
list_deployments
Lists deployments for a specific project, environment, and service
list_projects
Lists all Railway projects accessible by the token
list_variables
Lists environment variables for a service
restart_service
Restarts a running service instance
trigger_deploy
Triggers a new deployment for a service
whoami
Retrieves the authenticated Railway user profile
Example Prompts for Railway in Windsurf
Ready-to-use prompts you can give your Windsurf agent to start working with Railway immediately.
"List all active projects on my Railway account."
"Restart the deployment for the ECommerce Backend service."
"Has the latest Production build finished yet?"
Troubleshooting Railway MCP Server with Windsurf
Common issues when connecting Railway to Windsurf through the Vinkius, and how to resolve them.
Server not connecting
Railway + Windsurf FAQ
Common questions about integrating Railway MCP Server with Windsurf.
How does Windsurf discover MCP tools?
mcp_config.json file on startup and connects to each configured server via Streamable HTTP. Tools are listed in the MCP panel and available to Cascade automatically.Can Cascade chain multiple MCP tool calls?
Does Windsurf support multiple MCP servers?
mcp_config.json. Each server's tools appear in the MCP panel and Cascade can use tools from different servers in a single flow.Connect Railway with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
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Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Railway to Windsurf
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.
