How to secure MCP tools on AWS for AI agents with authentication, authorization, and least privilege

Model Context Protocol (or MCP) makes it easier for AI agents to access your existing backend capabilities. It allows AI agents to have access to your system's call services and to use tools such as Lambda functions. That convenience comes with a huge trade-off, a raised bar for security, because it demands a much stronger access model around those interactions. The problem is that once an agent can reach tools, you should be questioning who is calling what, on whose behalf, with which scope, through which boundary, and, most importantly, how to stop the whole thing from becoming an overprivileged mess and ruining the experience for real humans using your product. The issue is clearly there and AWS is already building for this through Bedrock AgentCore Gateway and AgentCore Identity, while the MCP roadmap is moving in the same direction with enterprise-managed auth, audit trails, gateway patterns, and more fine-grained least-privilege scopes. But authentication is no longer the main ev