The MCP Automation Stack
From natural language to real-world action in five layers
MCP is the bridge between AI agents and real-world services. Without MCP, an AI agent can only generate text. With MCP, it can query your database, update a spreadsheet, send a Slack message, and deploy code, all in a single conversation.
If you haven't explored MCP yet, the MCP Development 101 course covers building servers from scratch. This module focuses on using existing MCP servers as automation building blocks.
The architectural insight behind MCP is composability. Each MCP server exposes a focused set of tools for a single service: Google Sheets, Slack, PostgreSQL, GitHub. An AI agent can discover available tools at runtime and chain them together to accomplish goals that no single tool was designed for. A prompt like "pull last week's signups from the database, calculate conversion rates, update the metrics sheet, and post the summary to the team Slack" requires four MCP servers working in sequence, but the agent orchestrates the entire flow from a single natural language instruction.
MCP Server Catalog
Production-ready MCP servers for common automation targets
Tools: read, write, create, search cells
Tools: post message, read channels, react
Tools: query, insert, update, schema
Tools: create PR, read issues, merge, search
Tools: read, write, list, search, move files
Tools: navigate, click, screenshot, read page