Connection Layer (MCP)
A simple guide to MCP, the protocol that lets AI tools talk to the outside world.
Start with What a Tool Actually Is →Getting Started2 questions
What a Tool Actually Is
In plain terms, why AI needs tools, and the actual path a request takes from you, to the agent, to the AI, and back again.
Why MCP Exists
The integration problem the Model Context Protocol solves, and the three primitives it standardizes: tools, resources, and prompts.
How It Works2 questions
How the Pieces Fit Together
The host, client, and server roles in MCP, how they talk over JSON-RPC, and what a full request actually looks like end to end.
MCP, RAG, and Plain APIs
What MCP is actually for compared to retrieval-augmented generation, traditional API integrations, and agent frameworks, and when to combine them.
Building With It3 questions
Building Your First Server
A hands-on walkthrough of writing a small MCP server from scratch and connecting it to a real AI assistant.
Tools, Resources, and Prompts in Practice
Dynamic tool discovery, letting a server ask the model something mid-task, resource URI design, and writing prompts that actually guide a workflow.
Designing Tools People Actually Use
Why goal-oriented tools beat granular ones, and how a tool's description determines whether an AI model uses it correctly.
Running It Well3 questions
Security and Trust Boundaries
Authenticating and authorizing tool calls, defending against prompt injection through tool input, and rate limiting a server against abuse.
Performance at Scale
Caching, connection pooling, batching, and token-efficient responses for an MCP server under real production load.
Rolling MCP Out on a Team
A four-stage path for adopting MCP inside a real organization, the pitfalls that show up at each stage, and what to actually measure.