Automated agent evaluation with Amazon Bedrock AgentCore and GitHub Actions
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Wire Amazon Bedrock AgentCore Evaluations into a GitHub Actions pipeline: deploy an AI agent and an OAuth-protected MCP server to AgentCore runtime, invoke the agent with test prompts, score the responses, and automatically block pull requests when agent behavior regresses.
Build a continuous integration and continuous delivery (CI/CD) quality gate that deploys an agent with role-based MCP tools, evaluates it, and blocks PRs when evaluation scores drop. You shipped an AI agent on Amazon Bedrock AgentCore runtime . It calls tools through an MCP server protected by OAuth. Now you want CI to tell you when a code change makes its performance worse before it reaches production. This post walks through a GitHub Actions pipeline that deploys an agent to AgentCore runtime…
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