What problem does it solve?
LLMs cannot natively interact with external services, APIs, or databases, creating a critical gap between AI capabilities and real-world data access. This skill provides a complete, production-grade guide to building Model Context Protocol servers that bridge this gap and enable seamless LLM-to-service integration.
Core Features & Use Cases
- Dual-Language Implementation: Comprehensive, production-ready guides for both TypeScript (MCP SDK) and Python (FastMCP) server development.
- Design Best Practices: Expert patterns for tool naming, input validation, error handling, pagination, response formatting, and security hardening.
- Evaluation Framework: Complete workflow for creating rigorous test suites that validate whether LLMs can effectively use your MCP server to answer complex, realistic questions.
- Use Case: A developer needs to expose a custom CRM API to an LLM agent. This skill walks through the entire process from studying the API documentation to implementing tools, adding validation, and creating evaluations to ensure quality.
Quick Start
Use the mcp-builder skill to create a new MCP server that exposes your external API to LLMs.
