Universal Trust Adapter unifies credential verification for AI agents across 8 standards

AliceLabs has released the Universal Trust Adapter (UTA), an open-source library designed to standardize trust verification between AI agents that invoke tools, APIs, and microservices. The core problem UTA addresses is that existing credential standards — including JWT, W3C Verifiable Credentials, X.509, and Google's A2A Protocol — each answer identity and scope questions differently, leaving AI agents without a common verification method. UTA accepts eight credential formats and processes them through a 12-stage pipeline, achieving over 6,700 verifications per second on a single CPU core. The library is available on GitHub and npm under the package name @marketnow/trust-core, with a public REST API for testing. The developers note key limitations: UTA handles cryptographic verification but does not determine whether an issuer is trustworthy, and support for EAT-AI and ZTA formats remains in beta.