Accelerate AI Agent Development with Bedrock AgentCore MCP Server

Amazon Bedrock introduces the AgentCore Model Context Protocol (MCP) Server, a significant advancement designed to drastically accelerate the development and deployment of AI agents compatible with Bedrock AgentCore. This server provides built-in support for runtime, gateway integration, identity management, and agent memory, enabling rapid prototyping, production-grade solutions, and enterprise-scale agent infrastructure. It aims to transform agent development by integrating seamlessly with agentic IDEs like Kiro, Cursor, and Claude Code, allowing developers to complete complex tasks—such as learning Bedrock AgentCore services, integrating runtime and tools, managing security, and deploying—in minutes using conversational commands.

Key features of the AgentCore MCP Server include automating the complete agent lifecycle and eliminating the steep learning curve. It intelligently transforms existing agents for AgentCore Runtime integration, guiding coding assistants on necessary functional changes like adding library imports, updating dependencies, initializing applications, and converting entrypoints while preserving original logic. The server also automates development environment provisioning, handling dependency installation (bedrock-agentcore SDK, starter-toolkit CLI, strands-agents SDK), AWS credential configuration, execution role definition, ECR setup, and `.bedrock_agentcore.yaml` file creation. Furthermore, it simplifies tool integration with Bedrock AgentCore Gateway for cloud communication and enables straightforward agent invocation and testing via natural language commands within the IDE.

Developers benefit from reduced friction and faster innovation cycles. The server promotes a layered architecture for comprehensive AI agent development support, ranging from agentic IDEs to specific framework and SDK documentation, and steering files for complex workflows. Installation involves a simple configuration in an IDE’s `mcp.json` file. The server facilitates an entire agent development lifecycle, from preparing agent code (e.g., Strands Agents, LangGraph) to transforming, deploying via AgentCore CLI, and testing, including modifying agents to utilize deployed AgentCore Gateway MCP servers. This streamlines the creation, iteration, and deployment of intelligent AI applications on AWS.

(Source: https://aws.amazon.com/blogs/machine-learning/accelerate-development-with-the-amazon-bedrock-agentcore-mcpserver/)