Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

CISOs everywhere are feeling the AI fatigue. Every vendor at Black Hat 2025 was hyping ‘AI agents for SecOps,’ so there’s rightfully a lot of skepticism about deploying AI in production, especially in enterprise environments. But the old way of running a SOC just isn’t working anymore. After all the time and money spent on traditional playbooks, we’re still wrestling with the same challenges: alert fatigue, burnout, tool sprawl, and inability to scale.

Model Context Protocol (MCP) is gaining traction because it enables LLMs to interact with live systems and enhance context by retrieving and managing relevant real-time information. LLMs can’t query Salesforce, trigger an Okta password reset, or fetch context from your SIEM, for example. MCP bridges that gap by connecting AI models to real-world APIs, powering AI applications like retrieval-augmented generation and multi-step agent workflows. They’re fast to deploy.

AI is moving through enterprises faster than security teams can track. Over the past year, AI privacy incidents have risen 56%, and most of those stem from tools security never knew were in use. 84% of SaaS tools are purchased outside IT, and 62% of CISOs say fewer than a quarter of AI tools in use have been approved through procurement. That means sensitive, regulated, or confidential data is often flowing to AI services invisibly, sometimes across borders, without governance or guardrails.

The Model Context Protocol (MCP) is a standardized framework that enables large language models (LLMs) to interact with external tools, APIs, and data sources. While MCP offers powerful integration capabilities across software development, data analysis, automation, and security operations, it also introduces serious security risks. This post provides a technical overview of how MCP works, its architecture, and real-world use cases.

Egnyte AI agents are smart, task-specific AI assistants built to automate repetitive, time-consuming work, so that your team can stay focused on high-impact and strategic tasks. From reviewing documents to researching topics or translating content, these agents act like always-on digital coworkers who execute task-specific instructions while securely leveraging information contained in your private documents and on the web.