Chris Heilmann, Daniel Cranney & Tiffany Souterre
Build a Multi-Agent Role-Playing Game Master with Strands Agents
#1about 2 minutes
Understanding the fundamentals of AI agents
AI agents are large language models (LLMs) enhanced with the ability to perform actions using external tools.
#2about 2 minutes
Standardizing agent-tool communication with MCP
The Model Context Protocol (MCP) provides a standardized way for AI agents to connect with and use various tools, similar to REST APIs.
#3about 1 minute
Enabling agent collaboration with the A2A protocol
The Agent-to-Agent (A2A) protocol standardizes communication and collaboration between different AI agents.
#4about 2 minutes
Getting started with the Strands SDK for agents
The Strands SDK from AWS simplifies building multi-agent workflows by handling MCP and A2A protocols with just a few lines of code.
#5about 4 minutes
Creating a basic agent and using local models
Learn how to instantiate a simple agent and configure it to use different LLM providers, including local models via Ollama.
#6about 9 minutes
Adding capabilities with built-in and custom tools
Give agents new abilities by importing pre-built tools or creating your own custom functions using the `@tool` decorator.
#7about 5 minutes
Serving tools remotely with an MCP server
Decouple tools from your agent by running them on a dedicated MCP server, making them accessible to any connected agent.
#8about 12 minutes
Building a multi-agent system with the A2A protocol
Create a collaborative system by running specialized agents on A2A servers and connecting them to a primary orchestrator agent.
#9about 3 minutes
Showcasing the complete multi-agent game master
A full demonstration shows a game master agent orchestrating a character agent, a rules agent, and a dice-rolling tool via a UI.
#10about 1 minute
Conclusion and resources for getting started
Find links to the Strands SDK documentation, code samples, and a discount code for AWS re:Invent.
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