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paper2023Unreviewed

Architecting MCP-Based Platforms for Enterprise-Scale Agentic Generative AI

Karthik Perikala

Journal of Business Intelligence and Data Analytics

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Abstract

Enterprise adoption of generative AI is rapidly shifting from isolated prompt-driven applications toward complex agentic systems that integrate retrieval, reasoning, and tool execution. As these systems grow in scale, the lack of a standardized interaction model between agents and external capabilities introduces challenges in reliability, observability, security, and operational governance. This paper presents aplat form architecture centered on the Model Context Protocol (MCP) as a first-clas

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Agentic Threats

Cite

@article{perikala2023architecting,
  title = {{Architecting MCP-Based Platforms for Enterprise-Scale Agentic Generative AI}},
  author = {Karthik Perikala},
  year = {2023},
  journal = {Journal of Business Intelligence and Data Analytics},
  doi = {10.55124/jbid.v2i3.264},
  url = {https://www.semanticscholar.org/paper/00a09f191759c2002a99a2d485d875d1b26859be}
}