In July, the MCP Server Builder community held two significant meetups in San Francisco and New York, engaging engineers, toolmakers, and AI developers in discussions and demonstrations on building with the Model Context Protocol (MCP) for large language models (LLMs). Key sessions included Nina Lopatina's exploration of dynamic server selection using Contextual AI, Annie Wang's demonstration of Google's Agent Development Kit for simplifying the agent lifecycle, and YK Sugi's presentation on AI-driven UI testing with MCP servers. Michael Watson of Apollo showcased the efficient management of MCP servers with tools like hot-reloading, while Diptanu Gon Choudhury highlighted the protocol's role in scalable, stateful workflows. Other sessions covered using Postman's Flows for DevOps automation, securing MCP servers with zero trust principles by Nick Taylor, and voice-to-voice agent interactions by Hermes Frangoudis. The events highlighted the potential of MCP in enhancing agentic workflows and emphasized community collaboration to further develop and implement advanced MCP tools.