mcp-builder

This skill guides the development of MCP servers by providing architectural patterns, SDK-specific implementation strategies, and automated evaluation harnesses. It facilitates external service integration into LLM workflows through structured tool definitions and schema design.

The best way to structure a Model Context Protocol server is by following a four-phase workflow: research, implement, test, and evaluate. It provides specific guidance and best practices for both Python FastMCP and TypeScript Node SDKs.

Model Context Protocol server performance is ensured by enforcing best practices for tool naming, error handling, and schema design. An automated evaluation harness tests tool effectiveness to verify LLMs can perform complex, multi-step tasks.

Yes, you can use FastMCP to integrate external services into LLM workflows. The skill offers specific guidance and best practices for the Python FastMCP SDK to facilitate reliable external service interactions.

You test MCP server effectiveness for multi-step LLM tasks using a built-in evaluation harness. This quality assurance component tests tool effectiveness to ensure LLMs can successfully perform complex, multi-step operations.

You need input validation and pagination logic in an MCP server to facilitate reliable integration of external services into LLM workflows. These structured definitions ensure high-quality server performance and robust error handling.