A Survey of the Model Context Protocol (MCP): Standardizing Context to Enhance Large Language Models (LLMs)

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Abstract

The Model Context Protocol (MCP), recently introduced by Anthropic, proposes a standardized framework for integrating large language models (LLMs) with dynamic external systems. This survey reviews the foundational architecture of MCP, including its client-server model, standardized messaging protocols, dynamic tool discovery, and security mechanisms, against the backdrop of current, fragmented API solutions. Although the protocol promises enhanced interoperability and scalability for Agentic AI systems, data supporting its long-term performance remains limited. MCP’s design is critically evaluated, potential applications in domains such as finance, healthcare, and customer service are discussed, and the key challenges are outlined. This work aims to inform researchers and practitioners of MCP’s potential benefits and its present limitations in the evolving AI integration landscape. The GitHub link for this survey is: Model-Context-Protocol-Survey.

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