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MCP Security in Practice: Prompt Injection, Least Privilege, and Audit Logs

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Connecting an AI agent to internal tools is the first time most teams confront a security boundary that is not enforced by code alone. Traditional programs take instructions from developers and data from users; an LLM-driven agent takes instructions from both, and it cannot reliably tell them apart. A field value, an issue comment, a web page, or a tool description can all contain text that changes what the model does next. The Model Context Protocol does not solve this; it makes the boundary explicit so you can secure it. This article is a practical threat model for teams shipping MCP servers

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