Merge's blog post discusses the Model Context Protocol (MCP), which enables large language models (LLMs) to access data and functionality in various products through an MCP server. The post outlines the process of building an MCP server, highlighting the importance of implementing both list_tool and call_tool functions, which facilitate the discovery and invocation of tools within the server. An MCP tool executes predefined functions for LLMs, requiring a name, description, and input schema, while list_tool and call_tool functions help users discover and utilize these tools effectively. The post also emphasizes the benefits of Merge MCP, which allows LLMs to access over 220 applications securely and efficiently by writing minimal code, and includes features like Integration Observability and advanced syncing to manage integrations and maintain data accuracy. The discussion underscores the challenges and considerations involved in developing a robust MCP server and suggests that Merge's platform not only serves as a Unified API product but also as a comprehensive integration management platform.