How to secure your remote MCP server on Google Cloud
As enterprises increasingly adopt model context protocol (MCP) to extend capabilities of AI models to better integrate with external tools, databases, and APIs, it becomes even more important to ensure secure MCP deployment. MCP unlocks new capabilities for AI systems; it can also introduce new risks, such as tool poisoning, prompt injection, and dynamic tool manipulation. These can lead to data exfiltration, identity subversion and misuse of AI systems. Securing an MCP deployment begins with a strong security foundation. Here are five key MCP deployment risks you should be aware of, and how using a centralized proxy architecture on Google [...]