mcp-server-patterns

The mcp-server-patterns skill provides a structured approach for building and maintaining Model Context Protocol (MCP) servers using the Node/TypeScript SDK. MCP enables AI assistants to interact with external systems through well-defined interfaces such as tools, resources, and prompts. This skill focuses on helping developers implement servers that expose these capabilities in a consistent way, allowing models to execute actions, retrieve contextual data, and use reusable prompt templates. It addresses the complexity of connecting AI systems to backend services while maintaining a clean separation between server logic and transport mechanisms.

The skill highlights key capabilities including defining tools for executable actions, resources for read-only data access, and prompts for reusable templates that can be surfaced in client applications. It also emphasizes input validation using Zod or SDK-supported schema systems to ensure reliable and safe tool execution. Additionally, it covers transport options such as stdio for local environments (e.g., desktop AI clients) and Streamable HTTP for remote deployments, while noting that SDK APIs may vary across versions and should be verified against official documentation or Context7. Best practices such as schema-first design, structured error handling, idempotency, and version pinning are also central to its usage.

This skill is intended for developers building AI-integrated backend services, particularly those working with MCP-compatible clients like desktop or cloud-based AI tools. It is also useful for engineers upgrading MCP SDK versions, debugging server registration issues, or designing modular AI tool ecosystems. By following these patterns, users can create scalable and maintainable MCP servers that integrate seamlessly with evolving AI agent frameworks.