The Model Context Protocol has no built-in input sanitization, argument sensitivity classification, or trust-boundary validation at the protocol layer, forcing every server implementor to independently solve the same security primitives—and consistently failing to do so. With 200k+ servers and 150M+ downloads, the attack surface is systemic: multiple independent CVEs (credential exposure, path traversal, SSRF, command injection) share the same root cause of missing protocol-level guarantees. A security middleware or capability attestation layer sitting between MCP clients and servers could create network effects by raising the floor for all implementations simultaneously.

Every MCP server independently reimplements input sanitization, trust boundaries, and argument validation—and most get it wrong, creating systemic CVEs across 200k+ servers that share identical root causes.

MCP server developers and enterprises deploying AI agents that connect to MCP tool servers in production environments.

Security teams at companies adopting MCP agents are already blocking deployments due to unaudited tool servers; a drop-in middleware that enforces validated security policies converts compliance blockers into instant approvals, and enterprises routinely pay for security middleware (WAFs, API gateways) in analogous positions.

Ship a lightweight proxy (Rust/Go) that sits between MCP client and server, enforcing a declarative policy schema covering input sanitization, argument sensitivity classification, path traversal prevention, SSRF blocking, and credential redaction—bootstrapped with community-contributed attestation profiles per popular server type, published to an open registry.

With 150M+ MCP downloads and enterprise AI agent adoption accelerating, this sits in the API security / runtime application security market (~$8B) at the exact new chokepoint where agents meet tools.