This article details the Model Context Protocol (MCP), an open standard for connecting AI agents to tools and data across enterprise landscapes. It covers MCP implementations by AWS, Azure, and Google Cloud, security considerations, and the growing ecosystem surrounding the protocol.
A review of a Google paper outlining their framework for secure AI agents, focusing on risks like rogue actions and sensitive data disclosure, and their three core principles: well-defined human controllers, limited agent powers, and observable actions/planning.
The article details five security vulnerabilities in the Model Context Protocol (MCP): Tool Poisoning, Rug-Pull Updates, Retrieval-Agent Deception (RADE), Server Spoofing, and Cross-Server Shadowing. It explains how these vulnerabilities could compromise user safety and data integrity in AI agent systems.
An article discussing ten predictions for the future of data science and artificial intelligence in 2025, covering topics such as AI agents, open-source models, safety, and governance.
