Abstract
This idea introduces an architecture for dynamically discovering, automatically installing, loading, and orchestrating Model Context Protocol (MCP) servers in response to user prompts in AI-driven applications. Unlike traditional MCP implementations that preload all available servers at startup, this approach enhances the user experience by automatically discovering missing MCP servers, auto-installing, and loading the MCP server with the AI application to accomplish the desired outcome for the user. This technique allows natural language and intent to determine the necessary MCP servers needed and abstracts the rest of the complexities for the user, allowing them to focus on prompting naturally.
Creative Commons License
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Recommended Citation
INC, HP, "Dynamic, Prompt-Aware Orchestration and Lazy Loading of AI Model Context Protocol (MCP) Servers for Large Language Model (LLM) Applications", Technical Disclosure Commons, (August 27, 2025)
https://www.tdcommons.org/dpubs_series/8513