MCP lets AI systems interact with external tools and resources through standardized interfaces. MCP itself is not inherently insecure; it expands what an AI system can do, which makes the action boundary more important.
AI↓Choose tool↓Provide arguments↓Execute operation↓Receive result
Six questions for the new boundary
- Tool access: Which tools can this agent access?
- Action authorization: What can it do with each tool?
- Argument validation: Are parameters safe and expected?
- Human approval: Which operations need explicit authorization?
- Credential protection: How are upstream credentials handled?
- Auditability: Can the organization reconstruct what happened?
A governed path
AI Agent↓CustosPolicy → ALLOW / APPROVAL / DENY↓MCP / API / Internal Tool↓Audit
Custos is one way to place policy, approval, controlled execution, and audit around connected tool calls. It is not an official MCP security standard, and it does not make every connected system secure by itself.
KEY TAKEAWAY
MCP expands the action surface. Appropriate governance keeps that new boundary understandable and controlled.