A conversational time series forecasting assistant with Amazon Bedrock and LibreChat

Dashboards and reports remain the default interface for most forecasting systems, but they limit users to prespecified queries and views. In this post, we walk through the implementation of a conversational time series forecasting assistant built with ClickHouse, Amazon Bedrock, and LibreChat . This approach enables users to explore time series data interactively and adjust forecast parameters — such as quantile levels and prediction horizons — through natural language. The solution is built around the Model Context Protocol (MCP) , which defines a standard interface for connecting language models to external tools and services. Three MCP servers handle the core functionality: the official ClickHouse MCP server for data retrieval, a custom forecasting server wrapping Chronos - a time series foundation model developed by Amazon - on Amazon Bedrock, and a custom data visualization server for interactive Plotly charts. Claude Sonnet 4.6 on Amazon Bedrock orchestrates the tool calls. The v