ha-mcp

This capability allows users to define functions using a schema that integrates with multiple AI model providers. It utilizes a model-context-protocol (MCP) to standardize interactions, enabling seamless function calls across different AI services. The architecture supports dynamic routing of requests based on the schema, allowing for flexible integration with various models without needing to rewrite code for each provider.

This capability manages the context for different AI models by maintaining a stateful session that tracks user interactions and preferences. It uses a centralized context store that can be accessed and modified by various components of the application, ensuring that the model's responses are relevant and tailored to the user's needs. This architecture allows for a more personalized experience as it adapts to user behavior over time.

This capability orchestrates API calls dynamically based on user-defined workflows, allowing for complex interactions with multiple AI services. It leverages a rule-based engine to determine the sequence of API calls and manage data flow between them, ensuring that the right data is passed at each step. This architecture supports both synchronous and asynchronous operations, providing flexibility in how workflows are executed.