settlegrid-discovery

This capability enables seamless integration of various AI model contexts through a unified MCP (Model Context Protocol) architecture. It utilizes a flexible schema-based approach to define and manage interactions with multiple AI providers, allowing for dynamic context switching and integration without extensive reconfiguration. The architecture is designed to facilitate easy onboarding of new models and providers, enhancing interoperability across diverse AI ecosystems.

This capability allows for real-time management of context information across multiple AI models, utilizing a centralized context store that updates dynamically based on user interactions. The system employs event-driven architecture to listen for context changes and propagate updates to relevant models, ensuring that each model operates with the most current context available. This reduces latency and improves the accuracy of model responses.

This capability orchestrates API calls to various AI models using a schema-driven approach, allowing developers to define the structure and flow of API interactions declaratively. By leveraging a centralized schema registry, the system can validate and transform requests and responses, ensuring compatibility across different models. This reduces the need for custom code for each integration, streamlining the development process.