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Revamp Your MCP Architecture: Integrate MCP Servers with AgentCore Gateway

Enhancing AI Workflows with Unified MCP Server Integration

Simplifying Tool Management Across Enterprises

Introducing Amazon Bedrock AgentCore Gateway

Breaking Down MCP Silos: Why Enterprise Teams Need a Unified Gateway

AgentCore Gateway Integration Architecture

Solution Walkthrough

Get Started with Adding MCP Server into AgentCore Gateway

Prerequisites

Create a Gateway

Create a Sample MCP Server

Configure AgentCore Runtime Deployment

Launch MCP Server to AgentCore Runtime

Create MCP Server as Target for AgentCore Gateway

Test Gateway with Strands Agents Framework

Refreshing Tool Definitions of Your MCP Servers in AgentCore Gateway

Conclusion

About the Authors

Unlocking the Power of AI: Integrating Model Context Protocol Servers with Amazon Bedrock AgentCore Gateway

As AI technology continues to be adopted at scale, organizations are finding themselves managing a multitude of specialized Model Context Protocol (MCP) servers tailored to various agent use cases, domains, and organizational functions. These servers, which are pivotal in optimizing AI workflows, require a streamlined approach for integration to enhance performance and operational efficiency.

The Need for a Unified Approach

Without a centralized system, organizations may struggle with fragmented tool discovery and sharing. The complexity of managing authentication across multiple MCP servers can quickly become overwhelming. Each server may possess unique requirements related to access management, complicating how AI agents interact with various tools. Enter the Amazon Bedrock AgentCore Gateway—a robust solution designed to address these challenges.

Earlier this year, we launched the AgentCore Gateway, providing a centralized MCP tool server that offers a unified interface for agents to discover, access, and invoke tools. The recent extension of support for existing MCP servers within AgentCore Gateway marks a significant advancement. This allows organizations to group multiple task-specific MCP servers under a single, manageable interface, reducing operational complexities while maintaining existing security and authentication protocols.

Breaking Down MCP Silos: Real-World Application

Consider an e-commerce system where different teams maintain specialized MCP servers:

  • Shopping Cart Team: Handles cart management tools.
  • Product Catalog Team: Manages product browsing and search functionalities.
  • Promotions Team: Operates solutions for promotional logic.

Previously, interacting with these specialized servers required an ordering agent to navigate each connection separately, complicating authentication and data handling. With the introduction of the MCP server target support in AgentCore Gateway, all these servers can be unified under one interface, simplifying access while retaining team-specific ownership and control.

Benefits of a Unified Gateway

This consolidated approach offers several advantages:

  • Business Unit Alignment: Organize servers by business units, maintaining clear ownership while providing a cohesive agent experience.
  • Security and Access Control: Simplifies the authentication complexity by managing access through a single interface, making it easier for authorized agents to connect to the necessary tools.

The synergy between disparate systems promotes flexibility and efficiency, empowering teams to maximize their resources.

Architecting Solutions with AgentCore Gateway

Target Integration and Authentication

In AgentCore Gateway, a target represents the APIs, Lambda functions, or other MCP servers. This architecture allows an organization to seamlessly integrate a variety of tool providers into a single interface, optimizing both performance and user experience.

Moreover, the gateway decouples inbound authentication from target systems, enabling agents to access various tools via a consistent entry point. This not only simplifies development but extends to federated scenarios as well.

Managing MCP Server Targets

The introduction of MCP server targets represents an evolution in capabilities. Organizations can now integrate tools from their MCP servers, combining traditional APIs and Lambda functions into a coherent environment that enhances both security and performance.

This flexibility allows for gradual migration strategies, where teams can adapt MCP-native implementations while ensuring the continuity of existing tools. The gateway’s built-in synchronization mechanisms ensure tool definitions are kept current, facilitating smooth operational transitions.

Solution Walkthrough: Getting Started

Setting up an MCP server target within AgentCore Gateway is straightforward:

  1. Prerequisites: Ensure you have the necessary permissions and configuration files ready.

  2. Create a Gateway: Use the AgentCore starter toolkit to create a gateway with default authorization configurations.

  3. Create an MCP Server: Implement a sample MCP server with essential tools that return static responses.

  4. Configure AgentCore Runtime: Use the starter toolkit to deploy your MCP server efficiently.

  5. Launch and Link: Connect your MCP server to the AgentCore Gateway, ensuring the integration aligns with security and operational best practices.

Keeping Tools Fresh: Synchronization API

Managing tools means ensuring that they remain relevant. The SynchronizeGatewayTargets API allows organizations to refresh tool definitions on demand. This not only optimizes resource utilization but also ensures that tools available to agents are up-to-date and functioning optimally.

Implicit Synchronization

Whenever a new target is created or an existing one updated, implicit synchronization enables the gateway to work with the latest tool definitions without delay, ensuring consistent operational readiness.

Conclusion

The introduction of MCP server support as a target type in Amazon Bedrock AgentCore Gateway heralds a new era in enterprise AI agent development. By offering a centralized, unified approach, organizations can decrease operational complexity while enhancing tool discovery and management.

For a deeper understanding and practical examples, check out our coding samples and the Amazon Bedrock AgentCore Gateway Developer Guide.

About the Authors

Frank Dallezotte, Ganesh Thiyagarajan, and Dhawal Patel—experts in AWS architecture and AI development—bring their extensive experience to guide organizations in simplifying and scaling their AI workflows.


Embrace the future of AI with a unified approach; simplify your workflow with the Amazon Bedrock AgentCore Gateway today!

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