SAFE-MCP is a newly established framework aimed at enhancing security for AI agents. It emerged from the need for coordinated efforts in cybersecurity as AI technology rapidly evolves. The framework standardizes connections between AI models and tools via the Model Context Protocol (MCP), which, while powerful, poses significant risks if misconfigured. SAFE-MCP was recently adopted by the Linux Foundation and the OpenID Foundation, marking a shift from a draft to a structured, community-driven project with governance from respected organizations. This development is timely, given the increasing regulatory demands for secure AI systems from bodies like NIST and CISA. The framework acts as a living catalog of tactics, techniques, and procedures (TTPs) related to MCP, providing a shared language for assessing risks and defenses in AI systems. It includes over 80 documented techniques, focusing on real threats like prompt manipulation and tool poisoning. The collaborative effort behind SAFE-MCP involves contributors from major companies like Meta and eBay, fostering an ecosystem that emphasizes community-driven security practices. Weekly hackathons and global collaborations enable the framework to adapt quickly to emerging technology challenges. SAFE-MCP outlines specific patterns for securing AI agents, akin to airport security measures. Key components include verifying identities through scoped tokens, scanning interactions for potential risks, enforcing context-aware policies, and ensuring observability through audit trails. These layers help maintain a balance between the speed of AI actions and necessary security controls. By providing clear guidelines and reusable security patterns, SAFE-MCP supports enterprises, developers, researchers, and policymakers in tackling the complexities of AI safety.