Model Context Protocol (MCP) is an emerging open standard developed by Anthropic, designed to enable large language models (LLMs) to interact seamlessly with external data sources, such as HR and payroll systems, through a structured interface. The Finch MCP Server, recently introduced, leverages this protocol to connect LLMs with employer data provided by Finch's API, thereby facilitating new applications in employment tech. MCP functions as an interface layer that allows AI agents to understand and use available tools, enhancing automation and operational efficiency in complex, data-rich environments. Unlike traditional APIs that facilitate data exchange between software systems, MCP enables LLMs to autonomously access and process real-time data, thus unlocking sophisticated, AI-driven workflows in HR, payroll, and benefits administration. With its potential to automate repetitive tasks, provide real-time insights, and ensure compliance with data security protocols, MCP is poised to transform how developers build AI-powered applications in compliance-heavy sectors. However, organizations must carefully consider data security and compliance implications when integrating MCP, ensuring that employer data is accessed only with explicit consent and that LLMs are selected based on stringent usage policies.