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Complex objects containing metadata and message sequences for rich, multi-turn LLM context.
Distinct from Structured Return Objects: Distinct from Structured Return Objects: focuses on rich, multi-turn context for LLMs rather than general function return structures.
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FastMCP is a Python framework designed for building servers that expose functions, resources, and prompts to AI models using the Model Context Protocol. It simplifies the development process by automatically deriving tool metadata, input schemas, and documentation directly from Python function signatures and type hints. The framework provides a unified container for managing these components, allowing developers to build modular applications that integrate seamlessly with AI assistants. The project distinguishes itself through its support for interactive, server-defined user interface compone
Returns complex objects and message sequences to provide LLMs with rich, multi-turn context.
This project is a comprehensive framework for building AI-powered applications, providing a unified toolkit for orchestrating language models, autonomous agents, and interactive user interfaces. It serves as a central library for managing the entire lifecycle of AI interactions, from initial prompt generation and model provider abstraction to complex, multi-step reasoning and tool execution. The framework distinguishes itself through its deep integration with frontend development, specifically by enabling generative user interfaces that render dynamic components directly from model outputs. I
Guide users through the generation of structured data objects based on model output using dedicated interface components.