AI Communication Protocols

Introduction

An AI communication protocol standardises how agents (and tools) talk. Anthropic's Model Context Protocol (MCP) is the emerging open standard; OpenAI Swarm and AutoGen define internal protocols.

Beginner analogy: HTTP for the agent world — once everyone agrees, integration becomes trivial.

Understanding the topic

Core concepts:

• MCP: open protocol for tools + context + sampling.
• A2A (Agent-to-Agent): emerging Google initiative.
• OpenAPI: still gold-standard for tools.
• Versioning and schema validation are mandatory.
• Pick a protocol; don't invent one.

Syntax reference

Visual workflow / architecture:

Client / Agent ─► MCP Server ─► Tools / Resources / Prompts
                         │
                         ▼
                    Auth, schema, sampling

Real-world use

Claude Desktop ships MCP support; Cursor and Zed are adding it; Anthropic publishes 100+ MCP servers.

Best practices

• Adopt MCP for tool exposure where possible.
• Validate every message with schema.

Common mistakes

• Inventing a custom protocol when MCP fits.

Hands-on exercise

Interview preparation — practice these questions:

• Q1. What is MCP?
• Q2. Why does the agent world need a protocol?
• Q3. Scenario: you want to expose internal tools to many agent clients. Pick a protocol and justify.