Merge's blog post delves into the intricacies of Model Context Protocol (MCP) connectors, elucidating their functions and challenges in AI agent workflows. MCP connectors serve as MCP servers, either provided by software solutions or third-party developers, enabling agents to access data and perform tasks securely. The text outlines how MCP connectors operate by detailing the authentication process and tool invocation using platforms like GitHub, Linear, Salesforce, and Slack. Despite their benefits, such as pre-built solutions and customizable tools, the blog highlights potential issues like poor tool implementation, faulty authentication mechanisms, and a lack of centralized control. Merge Agent Handler is presented as a solution to address these challenges, offering numerous pre-built connectors, customizable tools, and enhanced security and authentication features for streamlined agentic workflows. The discussion also covers the flexibility of MCP connectors, allowing for simultaneous connections to multiple servers and the management of tool access via Tool Packs, enhancing AI adoption without compromising security.