Amazon Quick, a generative AI-powered business intelligence service, now supports integration with time-series databases through the Model Context Protocol (MCP). This enhancement allows financial analysts to access market data using conversational language, eliminating the need for complex database queries. The integration is demonstrated using KDB-X, a high-performance time-series database built on kdb+. The solution involves setting up the KDB-X MCP server on an Amazon EC2 instance, which enables the KDB-X service to run continuously and execute queries against the database. Amazon Quick translates natural language queries into SQL statements and sends them to the KDB-X MCP server for execution. The process also includes using Amazon Bedrock AgentCore Gateway as an authentication and routing layer to secure the connection between Quick and the MCP server. Users can perform specialized tasks such as computing volatility, querying market data, or semantically searching SEC filings within KDB-X tables. The integration is designed to be scalable and applicable across various domains, including financial market analysis, IoT sensor monitoring, and DevOps performance dashboards. The solution requires an AWS account, Amazon Quick with an Author Pro subscription, and access to KDB-X. *Source: [awsml](https://aws.amazon.com/blogs/machine-learning/amazon-quick-integration-with-time-series-databases-for-market-intelligence-using-mcp/)*