How Zero-Trust Architecture Can Enforce Data Sovereignty in AI Agent Tool Calls

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Agentic AI systems that use tool-calling loops create new data egress paths with each external call, complicating regulatory compliance across jurisdictions. The Model Context Protocol (MCP), now widely used for agent-tool interoperability, is location-agnostic by design, making it a governance challenge for multi-region deployments. Organizations subject to regulations like GDPR, India's DPDP Act, or HIPAA cannot rely on prompt-level instructions to restrict data movement, as these are not enforceable security boundaries. A proposed approach on Google Cloud involves routing MCP tool calls through an inline reverse proxy on Cloud Run that evaluates agent identity, target server region, and payload sensitivity before allowing execution. This zero-trust model ensures that decisions about which tools an agent can call, with what data, and from which region are enforced at the infrastructure level rather than left to the AI model itself.

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