The text outlines an innovative approach to business intelligence (BI) that integrates a chat-native BI layer within Slack, utilizing ClickHouse and MCP to streamline data analysis and visualization directly in conversation threads. This method shifts the traditional BI focus from dashboards to conversations, allowing users to ask questions in natural language and receive both visualizations and SQL queries in response. The process leverages a Python bot to generate Vega-Lite visualizations, making it easy to create and share mini-reports within Slack without requiring users to learn complex BI tools or SQL syntax. This approach is designed to complement rather than replace traditional BI dashboards, offering a more fluid and rapid investigative tool for exploratory data analysis. The system's architecture benefits from ClickHouse's speed and scalability, while MCP ensures robustness and portability, allowing for seamless integration across different platforms. Despite limitations in complex visualizations, this practical solution enhances productivity by reducing friction in data-driven discussions, emphasizing its utility in exploratory and conversational analytics.