In this post, you build an AWS Support Companion using Amazon Bedrock AgentCore. The agent uses Strands Agents as the orchestration framework and connects to AWS services through the Model Context Protocol (MCP). By the end, you have a working agent that can analyze CloudWatch logs, search AWS documentation, query community knowledge from AWS re:Post, and create support cases, all from a single conversational interface. The solution deploys with a single script using AWS CloudFormation and includes a web frontend built on AWS Amplify for interacting with the agent.
The rapid advancement in AI agentic capabilities and the availability of sophisticated orchestration frameworks like AgentCore allow for the creation of practical, AI-powered support tools now.
This signifies a tangible step towards autonomous AI systems handling complex enterprise workflows, reducing reliance on human intervention for foundational support tasks and accelerating problem resolution.
Enterprises can now deploy custom AI agents capable of performing multi-step actions across various internal and external services, moving beyond simple chatbots to truly assistive autonomous companions.
- · AWS (Amazon)
- · Enterprises adopting AI agents
- · Developers building AI agents
- · Customer support functions
- · Manual IT support processes
- · Legacy knowledge management systems
Increased efficiency in AWS support and operations for users through automated assistance.
Broader adoption of AI agents for complex, multi-system tasks across various enterprise functions beyond just support.
A potential shift in workforce composition as AI agents take on more routine and diagnostic white-collar work, requiring humans to focus on higher-level problem-solving and innovation.
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Read at AWS Machine Learning Blog