Kogna MCP Server

This capability enables users to initiate and manage conversations with multiple AI avatars through a structured API that handles session state and context. It utilizes a room-based architecture to segregate conversations, allowing for seamless switching between avatars and rooms without losing context. The implementation leverages WebSocket for real-time communication, ensuring low latency and high responsiveness during interactions.

This capability allows users to switch between different AI avatars during a conversation, utilizing a lightweight state management system that tracks the current avatar context. The implementation is designed to minimize disruption, ensuring that the conversation flow remains intact even as the avatar changes. This is achieved through a centralized state store that updates the active avatar without requiring a complete refresh of the conversation.

This capability provides users with the ability to access and retrieve the history of their conversations with AI avatars. It employs a structured data storage system that archives conversations based on user sessions, allowing for efficient querying and retrieval. The implementation uses a RESTful API to fetch historical data, ensuring that users can access their past interactions quickly and reliably.

This capability allows users to query and manage system information related to the Kogna MCP Server, including available avatars, room configurations, and system status. It employs a modular design that separates system information from user interactions, allowing for dynamic updates and queries without impacting ongoing conversations. The implementation uses a combination of RESTful endpoints and WebSocket for real-time updates.