Model Context Protocol (MCP): Connecting LLMs to the Real World
The Model Context Protocol offers a standardized way to connect large language models to external tools and services, enabling more flexible, modular AI ecosystems where services can be composed and reused.
The Model Context Protocol (MCP), developed by Anthropic, offers a standardized way to connect large language models (LLMs) to external tools and services. At RISE, researchers are exploring how MCP can reliably bridge AI reasoning with real-world interaction.
How It Works
Instead of custom integrations for each system, MCP allows LLMs to issue structured function calls that tools can understand and respond to. This enables more flexible, modular AI ecosystems where services can be composed and reused across domains.
Demonstration
In a recent demonstration, RISE connected an IKEA Dirigera smart-home system to Claude LLM using MCP, allowing natural-language control of lights and devices. Using FastMCP, an open and lightweight framework, researchers can now build and test such integrations with only a few lines of code.
Security Considerations
The research highlights both the power and the risks of connected AI, showing that security, transparency, and authorization are essential as LLMs gain the ability to act in the real world.
