This framework serves as a bridge between backend services and AI agents by implementing the Model Context Protocol. It enables developers to expose existing application logic and web endpoints as standardized tools, allowing AI models to discover, interact with, and execute backend functions through a unified interface.
The project distinguishes itself by automatically converting application request and response models into protocol-compliant schemas, ensuring that AI agents receive accurate functional context. It supports a transport-agnostic architecture that facilitates real-time bidirectional communication via persistent HTTP streams and event-based methods, while allowing for the independent mounting of server interfaces to decouple communication layers from core service logic.
The framework includes comprehensive configuration options for managing service identity and filtering exposed operations to control access. It integrates directly with existing authentication and authorization flows to verify request identity, ensuring that only authorized entities can interact with the exposed tools. The library is designed to maintain compatibility with both modern streaming transports and legacy assistant implementations.
