Phase 3: Automation — MCP, Skills, APIs

🚀 What's Phase 3 About?

Phase 1 taught you how agents work. Phase 2 taught you how to prompt. Phase 3 teaches you how to connect Claude to everything else—APIs, databases, your tools.

This is where AI becomes actually useful. Agents that can only chat aren't agents—they're chatbots. Agents that can read your database, call APIs, and write files? Those are agents that work.

🔌 Part 1: MCP Protocol (The Game Changer)

MCP = Model Context Protocol. It's the standard way Claude connects to external systems.

Think of it like USB for AI. Instead of writing custom code to connect to GitHub, Slack, your database—you use MCP. It's standardized, it's fast, and it's the future.

What MCP Does

Claude calls your APIs automatically
Access databases in real-time
Read/write files on your system
All without you writing integration code

Common MCP Servers

GitHub (read PRs, write code)
Slack (read messages, send alerts)
Postgres (query databases)
Your custom servers

Why It Matters

No more "make an API call" workarounds
Claude can be trusted with real systems
Agents can actually do work
It's the standard everyone will use

Example: "Claude, read the last 5 GitHub issues, analyze them, and write a summary. Then post it in #ai-updates on Slack."

With MCP, Claude does all that automatically. No manual steps.

🛠️ Part 2: Skills (Reusable Workflows)

A "Skill" is a reusable function Claude can call. It's how you teach Claude to do repetitive tasks your way.

Why Skills matter:

Write once, use forever
Consistent output every time
Don't repeat instructions
Team members can reuse them

Example Skill:

Skill: "Analyze Product"
Input: product URL
Steps:
  1. Fetch product page
  2. Extract: price, reviews, description
  3. Compare to competitors
  4. Rate market fit 1-10
  5. Return formatted report

Claude can now call this anytime without repeating instructions.
    

You build skills in JavaScript or Python. Claude Code helps you write them.

🌐 Part 3: APIs (The Connectors)

Most useful data lives in APIs. Your SaaS tools, databases, cloud services—they all have APIs.

Common APIs Claude uses:

🐙

GitHub

Read code, create PRs

💬

Slack

Send messages

📧

Email

Send/read emails

📊

Sheets

Read/write data

🗄️

Postgres

Query databases

🔍

Custom

Your APIs

How it works: You give Claude API credentials (stored securely). It can then call APIs directly using MCP.

🚀 Your Phase 3 Project

🤖 Build an Automated Research Agent

What it does: You give it a topic. It researches it, finds sources, writes a report, and emails you the results—all automated.

What you'll learn:

Connect to Google Search API for research
Store findings in a database (Postgres or similar)
Send emails via SMTP
Set up MCP connections
Create a reusable Skill

End result: An agent you can ask "Research AI safety" and it handles everything.

Time to build: 8-10 hours

💡 Real-World Use Cases

🏢 Sales Team

Agent reads new leads, looks them up on LinkedIn, writes personalized emails, posts to Slack. All automated.

👨‍💻 Dev Team

Agent monitors GitHub issues, suggests fixes, writes code, creates PRs. Dev reviews and merges.

📊 Analytics

Agent pulls daily data from 5 sources, analyzes trends, sends reports. Every morning, ready to read.

🛍️ E-commerce

Agent monitors competitor pricing, updates your prices, alerts your team on price wars.

📚 What to Learn (In Order)

Step 1: MCP Basics

Understand what MCP is. Read the official protocol. See examples.

Step 2: Connect to 1 API

Pick one tool (GitHub, Slack, etc). Set up the MCP connection. Test it.

Step 3: Create a Skill

Build your first skill. Use it. Iterate. Make it perfect.

Step 4: Multi-API Agent

Combine multiple APIs. Build the research agent project.

📖 Getting Started

📘 Official MCP Docs

The complete guide to Model Context Protocol.

🔧 Claude Code Docs

How to build Skills with Claude Code.

🎓 Free Courses

Anthropic's official training on automation.

💬 Community

Join the community. Share your automations.

⚙️ Phase 3: Automation & Integration