MCP Protect takes the contract that's already been audited and scanned and turns it into a runtime policy — the same model 42Crunch has used to protect APIs for a decade, now applied to the traffic between AI agents and the tools they call.
Even though it looks similar to API security, it's a fundamentally different shape of problem: an attack against an MCP server — or against the business logic and data behind it — can be forwarded by the server and land on the AI agent itself. 42Crunch protects both sides.
The same discipline 42Crunch has applied to APIs for a decade: the approved contract becomes an allowlist. Anything a tool call attempts that the contract didn't declare — unauthorized data access, an out-of-scope operation, a bypass of a declared rate limit — is something the enforcement point is positioned to stop, in the same way an API firewall enforces an OpenAPI contract today.
The newer half of the problem: content that reaches the AI agent through a tool result or a tool description can steer its behavior — prompt injection, tool poisoning, a rug-pull swap between review and production. Enforcement on this side is about stopping malicious content from ever reaching the model, not just about controlling who can call which tool.
It only enforces what's already been declared and validated. Nothing reaches this stage without first going through MCP Contract generation, MCP Audit scoring, and MCP Scan live validation.
Declares what's allowed.
Scores the declaration.
Validates live behavior.
Enforces it, continuously — this page.