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WeAreDevelopers LIVE • Sep 30, 2025

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

Chris Heilmann , Daniel Cranney , Tiffany Souterre

Standardizing agent-to-tool communication eliminates redundant code. Learn how to architect a scalable, multi-agent RPG Game Master using Model Context Protocol and the open-source Strands SDK.

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#1 about 3 min

Defining autonomous agents and tool integrations

Adding external tools to conversational AI converts static text generators into actionable software entities.

#2 about 3 min

Standardizing agent communication with MCP and A2A

The Model Context Protocol and Agent-to-Agent protocol standardize connections between models, tools, and collaborating agents.

#3 about 4 min

Initializing a simple agent using the Strands SDK

Installing the Strands framework and instantiating an agent enables rapid connection to cloud-based language models.

#4 about 3 min

Executing query resolution with local Ollama models

Connecting the framework to a locally hosted model provides offline capabilities for localized testing.

#5 about 3 min

Importing built-in functions to overcome context limitations

Applying pre-built community tools to an agent provides real-time information access previously missing from training data.

#6 about 3 min

Writing and executing files dynamically with AI tools

Adding file manipulation capabilities lets models autonomously author, read, and execute external scripts directly.

#7 about 5 min

Creating custom agent tools using Python decorators

Wrapping a standalone Python function with a configuration decorator exposes internal application logic to model orchestration.

#8 about 6 min

Deploying custom functions onto an MCP server

Migrating native tools to a dedicated server endpoint enables standardized function consumption across disparate models.

#9 about 6 min

Building specialized sub-agents with the A2A server

Configuring an independent agent with focused prompts allows the system to delegate highly specific computational workloads.

#10 about 6 min

Connecting multi-agent systems for workflow orchestration

Passing endpoint parameters back to a master orchestrator empowers language models to collaboratively request tasks and exchange data.

#11 about 5 min

Testing the completed multi-agent database workflow

Deploying the fully assembled architecture showcases dynamic interactions spanning interface inputs, local APIs, and specialized knowledge bases.

Matching moments

3:03 min

Using large language models as tabletop game masters

Chris Heilmann +2 · LIVE

3:25 min

Understanding foundational concepts of LLMs, agents, and MCPs

Perf + AI

1:42 min

Standardizing autonomous agent logic with model context protocol

Timo Salm Timo Salm · WWC 2025

5:37 min

Architectural patterns for composing dynamic AI agents

Philipp Schmid Philipp Schmid · WWC 2025

2:02 min

Moving from playing with artificial intelligence to business implementation

Lee Stott · Coffee With Developers

1:32 min

Building autonomous functions with conversational agent frameworks

Modood Alvi · WWC 2025

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