Brad Axen

From A2A to MCP: How AI’s “Brains” are Connecting to “Arms and Legs”

One AI asks another to read 50 pages and summarize them. This isn't sci-fi—it's how multi-agent systems use protocols to solve complex problems together.

From A2A to MCP: How AI’s “Brains” are Connecting to “Arms and Legs”
#1about 4 minutes

Understanding the core loop of AI agents

AI agents operate in a continuous loop where the LLM generates tool calls as JSON, which are then executed and their results are fed back as the next prompt.

#2about 4 minutes

How Model Context Protocol standardizes tool integration

Model Context Protocol (MCP) provides a standard for agents to connect with external tools, benefiting both agent and tool developers by creating a unified ecosystem.

#3about 6 minutes

A practical demo of an agent using multiple tools

A demonstration shows the Goose AI agent using multiple MCP-enabled tools like Databricks and a file editor to query data and build a web dashboard.

#4about 4 minutes

Using agent recursion for better context management

Multi-agent systems use recursion, where a parent agent delegates tasks to sub-agents, primarily to manage and reduce the context window for improved performance and cost.

#5about 4 minutes

The role of the Agent-to-Agent (A2A) protocol

Google's Agent-to-Agent (A2A) protocol enables communication across different agents and organizations, with potential use cases in specialized tasks and front-end communication.

#6about 1 minute

The future of AI protocols and agent ecosystems

AI development is being shaped by protocols like the established MCP for tools and the emerging A2A for multi-agent systems, which will define future agent collaboration.

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Matching moments

Understanding core AI concepts like LLMs, agents, and MCPs
08:25 MIN

Understanding core AI concepts like LLMs, agents, and MCPs

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Understanding AI agents, MCP, and the Strands SDK
45:04 MIN

Understanding AI agents, MCP, and the Strands SDK

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Exploring AI agents and the Model Context Protocol
30:10 MIN

Exploring AI agents and the Model Context Protocol

Java Meets AI: Empowering Spring Developers to Build Intelligent Apps

Using the Model Context Protocol for AI agent integration
14:42 MIN

Using the Model Context Protocol for AI agent integration

How to scrape modern websites to feed AI agents

Building AI agents using the Model Context Protocol
13:27 MIN

Building AI agents using the Model Context Protocol

One AI API to Power Them All

Introducing key protocols for agent communication
08:16 MIN

Introducing key protocols for agent communication

Building AI Applications with LangChain and Node.js

How MCP enables modern AI agent mashups
04:50 MIN

How MCP enables modern AI agent mashups

MCP Mashups: How AI Agents are Reviving the Programmable Web

Standardizing agent-tool communication with MCP
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Standardizing agent-tool communication with MCP

Build a Multi-Agent Role-Playing Game Master with Strands Agents

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