AWS has 200+ services. When building MCP servers and AI Agents, you'll realistically touch fewer than 15. Here are the essential ones.
Think of AWS as a city. EC2 instances are your office buildings, S3 is the warehouse district, IAM is the security desk, and Lambda is a courier service that only shows up when you call it.
// The city analogy — keep it in mind as you read
A virtual computer in the cloud you can rent by the hour. You choose the OS, CPU, memory, and storage. Your MCP server can run on an EC2 instance 24/7.
🏢 Like renting an office — you get the space, you manage what's inside.
compute
Infinite file storage in the cloud. You create "buckets" (like folders) and store any files — PDFs, images, JSON, model outputs. AI Agents often read/write documents here.
📦 Like Google Drive, but for developers — accessible via code.
storage
Run code without managing servers. You write a function, deploy it, and AWS runs it only when triggered (HTTP call, file upload, schedule). You pay per invocation — great for MCP tools.
🚗 Like Uber — a driver only shows up when you need a ride, not parked outside 24/7.
compute
Controls WHO can do WHAT in your AWS account. You create Users (people), Roles (identities for services), and Policies (permission rules). The most important service to understand for security.
🔑 Like a keycard system — every door has rules about who can enter.
security
Access powerful AI foundation models (Claude, Llama, Titan) via API. No GPU management needed. AI Agents built on Bedrock can use tools, call APIs, and reason in multi-step workflows.
🤖 Like hiring a brilliant contractor — you give the task, they figure out the steps.
AI / ML
A fast NoSQL database — think of it like a giant key-value store that scales automatically. AI Agents often use it to persist memory, session state, or conversation history.
📒 Like a notebook with infinite pages — look up any entry instantly by its key.
database
Creates HTTP endpoints that trigger your Lambda functions. Your MCP server can expose tools as REST APIs that Claude calls over the internet, instead of running locally on stdio.
🏛 Like a reception desk — all visitors (requests) come through here before reaching anyone inside.
networking
Safely store API keys, database passwords, and tokens. Your MCP server fetches secrets at runtime — no hardcoding credentials in code or config files. Rotates secrets automatically.
🗝 Like a secure vault — only authorized apps can retrieve the combination.
security
Logs, metrics, and alarms for everything in your AWS account. When your MCP server errors or slows down, CloudWatch is where you look. Also lets you set alerts for unusual activity.
🩺 Like a health monitor strapped to your entire infrastructure.
monitoring
Stream real-time data at massive scale — events, logs, sensor data. AI Agents that need to react to live data (stock ticks, IoT sensors) consume Kinesis streams as their input.
🚰 Like a pipe carrying a constant flow of water — your code reads drops as they pass.
streaming
A message queue — producers drop jobs in, consumers pick them up. Lets different parts of your AI system communicate asynchronously without one waiting for the other.
📬 Like a mailbox — the sender drops a letter, the recipient picks it up when ready.
messaging
Your own private network inside AWS. You control which services are public-facing and which are internal-only. Keeps your MCP server and databases isolated from the open internet.
🏘 Like a gated community — you decide who gets a gate pass and what's visible from outside.
networking