Model Context Protocols in Adaptive Transport Systems: A Survey

A comprehensive survey examines the Model Context Protocol (MCP) as a standardized framework for bridging fragmented adaptive transport systems where diverse protocols and AI applications operate in isolation. The research reveals that traditional transport protocols have reached adaptation limits and proposes MCP's client-server architecture as the foundation for next-generation intelligent transport infrastructure.

This academic survey addresses a critical infrastructure challenge: the fragmentation of interconnected devices, autonomous systems, and AI applications across transport networks. Researchers have identified that existing transport protocols operate in isolated silos, preventing effective context-aware decision-making at scale. The Model Context Protocol emerges as a unifying paradigm that enables semantic interoperability through standardized JSON-RPC structures.

The fragmentation problem reflects broader challenges in IoT and autonomous systems deployment. As devices proliferate and AI systems become more sophisticated, the inability to share contextual information across protocols creates inefficiencies and limits intelligent adaptation. Previous solutions developed ad-hoc workarounds rather than addressing the fundamental architectural problem.

For the technology industry, this survey validates a shift toward standardized integration frameworks. Developers and infrastructure providers who adopt MCP-compatible architectures position themselves at the forefront of next-generation transport systems. The research demonstrates that MCP's design—client-server models with JSON-RPC communication—naturally suits AI-driven applications requiring real-time context propagation and distributed decision-making.

The proposed research roadmap signals increasing investment and development focus on standardized protocols for intelligent transport. Organizations building autonomous systems, smart city infrastructure, or connected vehicle platforms should monitor MCP adoption trends. The convergence toward MCP-like architectures suggests that proprietary protocol fragmentation becomes economically unviable, driving consolidation around standards-based solutions.

• →Traditional isolated transport protocols have reached their adaptation limits, necessitating unified integration frameworks
• →Model Context Protocol's JSON-RPC client-server architecture enables semantic interoperability across fragmented systems
• →AI-driven transport applications require integration paradigms uniquely suited to MCP's distributed context-sharing capabilities
• →Existing research has implicitly converged toward MCP-like architectures, signaling inevitable standardization
• →Next-generation intelligent transport infrastructure will depend on MCP as foundational technology