Pattern 20: MCP Server Creation

Building Custom Tools for Your AI Agent

Overview

MCP (Model Context Protocol) servers extend AI with custom tools tailored to your exact needs.

Why do this?

  • Give AI direct access to your tools and systems
  • Eliminate copy-pasting between AI and tools
  • Create reusable capabilities across AI platforms
  • Make AI exponentially more useful for your work

This pattern is transformative for repetitive workflows and specialized domains. Instead of manual bridging, you create seamless integrations.

Key Principles

  1. Start simple - One focused tool, one real problem
  2. Design for AI - Intuitive interfaces AI understands
  3. Handle errors - Clear failure messages
  4. Document well - Good descriptions enable correct use

Exercise: Build Your MCP Server

Create an MCP server for your daily workflow.

Steps:

  1. Identify need: Choose a task you repeat daily. What steps could AI automate with tools?

  2. Design interface: Define clear function names and parameters. Make it intuitive for AI.

  3. Build and test: Create server with AI’s help. Start with one tool, test, expand. Clear error messages.

Your Turn

Pick your own tool!

Examples:

  • Bug tracking: Connect to Jira/Linear. Functions: create_ticket(), comment_on_ticket()
  • Calendar: Read local calendar, summarize next meeting with attendees and agenda
  • Cloud ops: Interface with AWS/GCP. Functions: list_s3_buckets(), restart_ec2_instance() (dev only!)

Tip: See MCP quickstart. I use FastMCP.