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This Model Context Protocol (MCP) server bridges the powerful FAIM time series forecasting SDK with any AI assistant that supports the Model Context Protocol. It exposes foundation time-series models like Chronos2 and TiRex from the FAIM API, allowing AI assistants to perform zero-shot point, quantile, and sample forecasts. This integration empowers AI agents with advanced predictive capabilities for various data types, enhancing their ability to analyze and predict future trends and supporting data-driven decision-making.

Características Principales

• Exposes `list_models` and `forecast` MCP tools for AI assistants.
• Supports flexible 1D and 3D array input formats for time series data.
• Enables point, quantile, and sample probabilistic forecasting capabilities.
• Allows custom quantile levels for detailed risk assessment in forecasts.
• Integrates with FAIM API's Chronos2 and TiRex foundation time-series models.
• 1 GitHub stars

Casos de Uso

• Enhancing AI assistants with advanced time series forecasting capabilities.
• Integrating state-of-the-art time series models into LLM applications.
• Providing AI agents with tools to analyze and predict future trends for data-driven decision making.