The Model Context Protocol (MCP) is an open-source integration designed to connect large language models (LLMs) with external data sources or tools in a standardised, flexible and secure way.
It has a client-server architecture which allows MCP clients to facilitate connections between LLM apps and MCP servers, which provide the models with relevant data from data sources such as file systems, APIs or proprietary datasets.
To ensure the best level of security, several precautions should be considered when using MCP servers, including file, API key and source restrictions, as well as careful control of dependencies.
It is also crucial to manage permissions carefully, granting LLMs access only to the files they need and avoiding giving them access to root directories.
This approach ensures that the LLM only accesses the necessary data, which enhances both the security and performance of AI systems.