mcp-server-gelato

This capability allows for invoking functions defined in a schema, enabling seamless integration with various model providers such as OpenAI and Anthropic. It utilizes a registry pattern to manage function definitions and their respective parameters, ensuring that users can easily switch between different AI models without altering their codebase significantly. This approach streamlines the process of calling external APIs while maintaining a consistent interface for developers.

This capability manages the context for multiple AI models, allowing for stateful interactions across different sessions. It employs a context stack pattern to maintain the state of conversations or interactions, enabling the server to provide more relevant responses based on previous interactions. This is particularly useful in applications where maintaining user context is crucial for delivering personalized experiences.

This capability enables the server to dynamically orchestrate API calls based on user-defined workflows. It uses a workflow engine that interprets user-defined rules and conditions to determine the sequence of API calls, allowing for complex interactions and data flows between different services. This flexibility is essential for applications that require real-time data processing and integration of multiple APIs.