ClickHouse has shared an update.
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The company highlighted a technical approach for embedding business intelligence (BI) capabilities directly into Slack using ClickHouse and the Model Context Protocol (MCP). The described workflow allows users to ask natural language questions in Slack, which are then converted into SQL, executed against ClickHouse, and returned as visualizations generated via Vega-Lite specifications and rendered in Python with vega-altair. Results are delivered as images in Slack threads, with MCP used to keep query execution and guardrails close to the data source.
For investors, this update underscores ClickHouse’s focus on enhancing developer-centric and AI-driven analytics workflows, potentially increasing the stickiness of its database offering within enterprise environments. By enabling “agentic” BI that fits into existing collaboration tools, ClickHouse is positioning its technology as a foundation for conversational analytics, an area of growing interest as organizations look to operationalize large language models in data workflows. While the post does not disclose commercial metrics, product launches, or new pricing, the emphasis on integrating with widely used tools like Slack and leveraging MCP suggests an effort to expand use cases and developer adoption, which could support future customer growth and higher usage-based revenue. Strategically, this reinforces ClickHouse’s standing in the competitive analytics database market as a platform that can power modern, AI-assisted BI experiences rather than only traditional dashboard-centric analytics.