clickhouse-mcp
The clickhouse-mcp server provides MCP access to ClickHouse columnar OLAP databases, enabling AI models to execute SQL queries and manage data tables. Data analysts and engineers use it to query petabyte-scale datasets for real-time analytics, aggregations, and reporting in AI-driven pipelines.
Overview
clickhouse-mcp is an MCP server that bridges large language models with ClickHouse, a columnar store for high-speed OLAP workloads. It exposes ClickHouse functionality through standardized tool calls, allowing models to read, write, and analyze massive datasets without custom integrations.
Key Capabilities
- execute_query: Runs SQL SELECT, INSERT, or other statements on ClickHouse tables, supporting complex aggregations and joins over billions of rows.
- list_tables: Retrieves metadata on databases, tables, and schemas for exploration.
- describe_table: Returns column schemas, data types, and engine details for a specific table.
- insert_data: Streams or batches data into ClickHouse tables using formats like CSV or JSON.
These capabilities leverage ClickHouse's vectorized query engine for sub-second responses on large-scale data.
Use Cases
- Real-time analytics dashboard: An AI agent uses execute_query to aggregate sales metrics from terabytes of event data, generating insights on demand.
- Data exploration: Developers invoke list_tables and describe_table to inspect schemas before building ETL pipelines.
- Log analysis: Security teams run execute_query on ClickHouse-stored logs to detect anomalies via SQL pattern matching.
- ML feature store: Engineers use insert_data to populate features from model outputs into ClickHouse for low-latency serving.
Who This Is For
Data engineers managing OLAP workloads, analysts querying high-volume data with AI assistance, and developers integrating LLMs into analytics stacks. Suited for teams handling clickstream, IoT, or time-series data in ClickHouse.