The Model Context Protocol (MCP) is rapidly becoming a standard for AI system connectivity, adopted by major tech companies like OpenAI and Microsoft. However, this rapid deployment has exposed critical security vulnerabilities, with many MCP servers lacking proper authentication. The text explores several security threats, including tool poisoning, cross-server shadowing, server spoofing, and token theft, and provides mitigation strategies for each. Tool poisoning involves embedding malicious instructions in tool descriptions, while cross-server shadowing allows a malicious server to influence legitimate servers' tool usage. Server spoofing can lead to token theft and data exfiltration, with attackers using nearly identical server names to deceive users. The "Lethal Trifecta" highlights how natural language instructions, autonomous tool calling, and access to sensitive data can lead to significant security breaches. Additionally, rug-pull updates occur when a trusted tool becomes malicious, often going unnoticed due to a lack of notification for changes. To address these vulnerabilities, the text emphasizes the importance of implementing robust authentication, secure token management, and comprehensive monitoring. Descope offers solutions to these challenges, including MCP Auth SDKs, agentic identity control, and secure OAuth 2.1 authorization, helping developers build secure AI systems efficiently.