arXiv:2508.19239v2 Announce Type: replace 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, si
The proliferation of interconnected devices, autonomous systems, and AI applications is creating severe fragmentation in adaptive transport systems, necessitating unifying protocols.
This survey identifies a foundational communication architecture for future AI and autonomous systems, potentially accelerating their development and interoperability across fragmented environments.
The focus shifts towards standardizing how AI systems interact and adapt to diverse contexts, moving beyond siloed development towards integrated architectures.
- · AI platform developers
- · Autonomous system manufacturers
- · Smart city infrastructure providers
- · Proprietary protocol developers
Improved interoperability and efficiency for adaptive transport systems and broader AI applications.
Faster deployment and scaling of complex AI-driven solutions across various industries.
Enhanced collaboration and data sharing among diverse autonomous components, leading to emergent system capabilities.
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Read at arXiv cs.AI