Implementing Agent Verse — From agents to Agent Registry to Agent Runtime to Agent verse.

Following up from the previous discussion from building agents to agent verse. let us look at step by step implementation

Start with building your agents:

In this case, we will consider building them using Amazon Bedrock. To learn more about understanding Agents, refer to this blog. This blog explains agent ecosystem and dives deep in to how Bedrock implements these patterns

To build bedrock agents with ease, Refer to this YouTube video. This video explains building a react agent with tools and knowledge bases (resources) at its disposal

However if you choose to build your agents using LangGraph, You can refer to this github repo for reference. This repo covers the different agent patterns in langgraph and how langgraph integrates with Bedrock Models, Tools and knowledge bases

Manage your agents — Agent Registry

In the agentic-verse, every LOB within an organization will be creating multiple agents. these agents can be dispersed across multiple AWS accounts / regions. A single pane of glass to view these agents are important for Governance, control and reusability. Refer to this github repo to build your agent registry

Run your agents — Agent Runtime

With multiple agents registered within the Agent Registry, you will now need an ability to select the right agent at run time based on the user query. An agent runtime that can select the agent at runtime and You can refer to this github repo to build your Agent Selection

Agnostic Agent Runtime

You can now extend this capability to a framework agnostic environment by exposing the agent selector capability as a Model Context Protocol (MCP) Server. You can refer to this github repo to expose the capability as a MCP Server

Closing thoughts:

Agent-verse is here to stay. A systematic approach to building, managing, invoking agents is key for sustainble growth in this hyper dynamic environment.