Model Context Protocols in Adaptive Transport Systems: A Survey

TL;DR

This survey explores the Model Context Protocol (MCP) as a unifying framework for adaptive transport systems, emphasizing its potential to address fragmentation and enable intelligent, context-aware communication.

Contribution

It systematically analyzes existing literature, introduces a taxonomy for MCP-related architectures, and positions MCP as essential for future adaptive transport systems.

Findings

Traditional protocols face adaptation limits

MCP enables semantic interoperability

AI-driven transport benefits from MCP integration

Abstract

The rapid expansion of interconnected devices, autonomous systems, and AI applications has created severe fragmentation in adaptive transport systems, where diverse protocols and context sources remain isolated. This survey provides the first systematic investigation of the Model Context Protocol (MCP) as a unifying paradigm, highlighting its ability to bridge protocol-level adaptation with context-aware decision making. Analyzing established literature, we show that existing efforts have implicitly converged toward MCP-like architectures, signaling a natural evolution from fragmented solutions to standardized integration frameworks. We propose a five-category taxonomy covering adaptive mechanisms, context-aware frameworks, unification models, integration strategies, and MCP-enabled architectures. Our findings reveal three key insights: traditional transport protocols have reached the limits of isolated adaptation, MCP's client-server and JSON-RPC structure enables semantic interoperability, and AI-driven transport demands integration paradigms uniquely suited to MCP. Finally, we present a research roadmap positioning MCP as a foundation for next-generation adaptive, context-aware, and intelligent transport infrastructures.