SOURCE-LINKED INTELLIGENCE
Zero-Trust Authorization and Discovery for Enterprise MCP
LLM agents translate natural-language context, which may include attacker-controlled text, into privileged tool calls, so authorization must remain effective even when an agent is prompt-injected or adversarially steered. The Model Context Protocol (MCP) has become a widely adopted interface for this boundary, yet its official SDKs' authentication and authorization primitives fall short of enterprise zero-trust requirements, most acutely a dual-persona model in which one server must serve human users (corporate SSO) and automated agents (service-account credentials on a different header). We c
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-18T20:51:19.000Z
First collected: 2026-09-23T12:01:45.602Z. This is not the publication date.