The Model Context Protocol (MCP) is emerging as a crucial framework for AI systems, enabling large language models to interact with external tools and data sources through standardized interfaces, reshaping how APIs are consumed. This transformation offers both opportunities and challenges, as AI agents can generate high volumes of requests, leading to potential resource overuse and revenue loss if not properly managed. Traditional pricing models like subscriptions are inadequate for the unpredictable usage patterns of AI, necessitating a shift towards usage-based monetization models that reflect resource consumption or value delivered. Moesif offers a solution for monitoring, metering, and monetizing MCP servers by providing real-time observability, integration with billing systems, and the ability to enforce usage limits, thus helping businesses manage AI-driven traffic efficiently and align costs with usage. Through Moesif, MCP traffic can be turned into revenue while maintaining transparency and governance, allowing for experimentation and gradual refinement of billing models without major architectural changes.