What problem does it solve? AI agents often fail to use external tools correctly because of vague tool names, untyped parameters, and poor error handling. This Skill guides the design and implementation of MCP servers so agents can reliably discover, call, and interpret custom tools that connect to APIs, databases, and business systems. ## Core Features & Use Cases - Agent-Friendly Tool Design: Enforces verb_noun naming, descriptive tool documentation, and typed parameter schemas using Zod (TypeScript) or Pydantic (Python). - Production-Grade Server Implementation: Provides runnable TypeScript and Python MCP server templates with structured error handling, environment-based secrets, and stateless tool design. - Resources, Prompts, and Testing: Covers exposing data as MCP resources, creating prompt templates, and testing the full agent tool-call loop including error paths. - Use Case: You need an agent to search support tickets. Use this Skill to build an MCP server exposing a search_tickets tool with validated status and priority filters, returning structured JSON the agent can act on. ## Quick Start Ask the agent to design and implement an MCP server in TypeScript that exposes tools for searching and updating records in your target API or database.