Intercept AI Agent Control

Example Use Cases

• 1

  Enforce strict, auditable policies on tool usage to prevent unauthorized or costly actions.

• 2

  That require rate limiting, spend tracking, and argument validation on API calls to MCP servers.

• 3

  Hide sensitive or dangerous tools from their accessible interface to reduce risk.

Description

Intercept acts as a proxy between AI agents and MCP servers, enforcing deterministic, stateful policies such as rate limits, spend caps, access controls, and argument validation on every tool call. It provides auditability, hot reload of policies, and hides unauthorized tools from agents to reduce attack surface and context usage. This ensures AI agents operate within defined constraints, preventing costly or dangerous actions.