API vs RAG vs MCP vs A2A Explained in 19 Minutes.

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RAG, MCP, and A2A solve three very different problems in AI agent development—but understanding how they work together is the key to building reliable, production-ready agents.

In this video, we build an imaginary travel assistant called Atlas and follow it through the complete AI agent stack:

- How APIs provide predictable software integrations
- How RAG gives agents fresh, relevant, and authorized knowledge
- How MCP connects AI applications to external tools and services
- How A2A enables independent agents to collaborate on complex tasks
- Why permissions, validation, user consent, and security still matter
- How all four layers work together in a real-world booking workflow

The simplest distinction:

RAG provides knowledge. MCP provides tools. A2A coordinates agents. APIs power the underlying services.**

By the end, you’ll understand where each technology fits, what it does—and what it does not do.

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Want to see the complete Atlas workflow built in code? Comment **“Atlas”** below.

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