Zero-Trust Security Frameworks for Model Context Protocol (MCP) Server Communications

Authors: SUNIL KARTHIK KOTA

DOI: https://doi.org/10.37082/IJIRMPS.v13.i6.232959

Short DOI: https://doi.org/hbq6wh

Country: United States

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Abstract: In the era of agentic artificial intelligence (AI), where large language models (LLMs) and autonomous agents invoke external tools and services through protocols such as the Model Context Protocol (MCP), the need for robust and rigorous security architectures is paramount. Conventional perimeter-based defenses are increasingly inadequate in these dynamic, distributed, and interconnected environments. This paper investigates the application of Zero-Trust Architecture (ZTA) principles to MCP server communications. We first analyze the threat surface introduced by MCP communications—the client-server interactions, tool invocations, context leakage, and lateral movement risks. We then propose a structured zero-trust framework tailored to the MCP ecosystem, encompassing identity and device verification, mutual authentication, micro-segmentation, dynamic policy enforcement, continuous monitoring, and breach containment. We provide a detailed architectural description, pseudo-code for policy evaluation, and complexity/scalability analysis. We also discuss deployment considerations in enterprise and cloud-native contexts.
Our contribution is three-fold:

(1) We bridge the gap between emerging AI agent-to-tool protocols (specifically MCP) and zero-trust security foundations.

(2) We propose a formalised zero-trust framework for MCP communications.

(3) We present an evaluative discussion of performance, scalability, strengths, and limitations. We conclude that zero-trust frameworks can significantly reduce risk in MCP deployments with manageable overhead, but real-world implementation requires rigorous identity, telemetry, and policy-management infrastructure.

Keywords: Zero Trust Architecture, Model Context Protocol, Agent-to-Tool Communication, Micro-segmentation, Mutual Authentication, Continuous Monitoring.

Paper Id: 232959

Published On: 2025-12-10

Published In: Volume 13, Issue 6, November-December 2025

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