Enables management of Railway infrastructure through 17 tools for managing projects, services, deployments, environment variables, and domains. Supports both modern Streamable HTTP and legacy SSE transports.
Enables deployment of autonomous AI agents with memory and tool execution capabilities through a WebSocket-based MCP protocol. Provides production-ready infrastructure with REST API access, persistent state management, and extensible function registry for building self-hosted AI systems.
Enables AI systems like Claude and Cursor to directly manage Railway projects, deployments, services, environment variables, and monitor logs through natural language commands.
Enables AI agents to manage Linear issues, projects, teams, users, comments, and cycles through an optimized interface designed specifically for language models. Supports both local and remote deployment with OAuth authentication and batch operations.
Enables AI agents to manage Linear workspace resources such as issues, projects, teams, cycles, and comments via Streamable HTTP MCP, with LLM-optimized tools and batch operations.
