What problem does it solve? AI agents often fail to use custom tools correctly because of vague names, untyped parameters, and poor error handling. This Skill guides the design and implementation of MCP servers so agents can reliably discover, call, and act on external APIs, databases, and services. ## Core Features & Use Cases - Agent-Friendly Tool Design: Enforces verb-noun tool naming, descriptive documentation, and typed parameters with Zod (TypeScript) or Pydantic (Python) so agents pick the right tool on the first try. - Production-Quality 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 to give an AI agent access to your support ticket system. Use this Skill to build an MCP server exposing search_tickets and get_ticket_stats tools with validated inputs and actionable error messages. ## Quick Start Ask the agent to design and implement an MCP server that exposes tools for your API, including typed parameters, descriptions, and error handling.