Resource Exposure Frameworks — Artificial Intelligence & Machine Learning

The Model Context Protocol is a standardized communication framework designed to connect language models to external data sources, functional tools, and interactive user interfaces. It provides a vendor-neutral interface layer that enables AI hosts to discover and execute capabilities across heterogeneous service environments, using a JSON-RPC based messaging standard to facilitate bidirectional communication between clients and servers. The protocol distinguishes itself through a robust capability-based handshake that negotiates feature sets during session initialization, ensuring compatibility and supporting graceful degradation when client and server capabilities are mismatched. It enforces security through a mediation framework that manages isolated connections, implements least-privilege access controls, and provides standardized authorization flows. By executing server instances as independent, host-managed processes, the protocol maintains strict security boundaries while allowing for modular growth through a defined lifecycle for protocol extensions. Beyond its core messaging and security primitives, the protocol covers a broad range of integration needs, including structured resource access, schema-defined tool invocation, and parameterized prompt templates. It supports advanced interaction patterns such as asynchronous task management with durable handles, interactive UI rendering, and dynamic user input elicitation. The ecosystem also includes developer tooling for session management, server metadata discovery, and diagnostic inspection to assist in the integration of local and remote services.