Anthropic's Model Context Protocol (MCP) is an open standard designed to enhance the integration of large language models (LLMs) with external data sources, enabling these models to perform more reliably and offer personalized outputs. The protocol consists of an MCP client that facilitates interactions between LLMs and data sources, and an MCP server that exposes data from both local and remote systems. MCP provides several benefits, such as simplifying the integration process, supporting workflow definitions, enhancing LLM efficiency, and strengthening security and compliance. However, it does not address certain areas like rate limit management, authentication, error handling, and support for webhooks. Unified API solutions complement MCP by offering features such as data normalization, security, observability, and performance enhancements, which together aid in managing customer integrations more effectively. Merge has released its own MCP server, Merge MCP, to provide access to over 220 integrations, ensuring seamless integration and management of customer-facing AI solutions.