Google is advancing its AI capabilities with the upcoming integration of an Apps rendering feature in Google AI Studio, enabling developers to build applications using its Gemini generative AI models. Concurrently, a new open standard called Model Context Protocol (MCP), developed by Anthropic and adopted by OpenAI, is gaining traction for securing AI workflows in enterprise environments. MCP acts as an interface similar to an API but is specifically designed for AI, allowing models to access diverse data sources and tools such as Workday, Salesforce, Slack, and Gmail while providing identity and security controls tailored for AI interactions. MCP facilitates seamless integration of external services, enhancing AI agents' ability to interact with various tools and data. Several tutorials and coding guides have been published demonstrating how to implement MCP servers and integrate them with Google Gemini 2.0 and other AI platforms. The protocol is seen as complementary to traditional APIs, supporting the evolution of AI agent infrastructure across both Web2 and emerging Web3 applications. Open-source MCP servers and developer resources are increasingly available, enabling broader adoption and innovation in AI tool connectivity and data pipeline automation.