The Railway MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Railway account. It provides structured and secure access to your projects, environments, services, deployments, logs, metrics, domains, and storage, so your agent can create infrastructure, deploy services, monitor performance, troubleshoot failures, and manage resources on your behalf.
- Project and environment setup: Have your agent create projects, build or clone environments, review staged changes, and commit approved environment updates.
- Service and deployment management: Let the agent create services from repositories, images, or templates, start deployments, check their status, cancel builds in progress, or remove completed deployments.
- Logs and troubleshooting: Direct your agent to inspect build, runtime, and HTTP logs, collect deployment evidence, and review deployment details when something goes wrong.
- Performance monitoring: Instruct your agent to examine HTTP traffic, response times, CPU, memory, disk, network, backup, and volume metrics for your Railway services.
- Domains, networking, and storage: Have your agent create or remove domains, configure buckets and private networking, and create, attach, or delete persistent volumes.