ClickHouse

High-performance columnar OLAP database for real-time analytics at petabyte scale.

MCPCLI1 Skill

About ClickHouse

High-performance columnar OLAP database for real-time analytics at petabyte scale. Explore how ClickHouse integrates with the agentic data stack ecosystem and supports autonomous data operations.

Key Features

  • Columnar storage with vectorized query execution for sub-second analytical queries
  • Real-time data ingestion handling millions of rows per second with low latency
  • Approximate query processing with HyperLogLog, quantiles, and sampling for fast estimates
  • SQL-compatible interface with extensions for arrays, maps, tuples, and nested data
  • Materialized views for incremental pre-aggregation and real-time data transformation
  • Tiered storage with hot/warm/cold data across local SSD, S3, and object storage
  • Linear horizontal scalability with distributed query execution across shards and replicas
  • Native integrations with Kafka, S3, PostgreSQL, MySQL, and 50+ data sources

Agent Integration

CLI — clickhouse-client

$ curl https://clickhouse.com/ | sh
CLI Documentation

External Links

ClickHouse MCP Server (Official)

Official MCP server for connecting ClickHouse to AI assistants — SQL execution, schema exploration, chDB support

ClickHouse Agent Skills (Official)

Official agentskills.io skills with 28 best-practice rules for schema design, query optimization, and ingestion

MCP Integration Guide

Official docs for configuring ClickHouse MCP with Claude Desktop, Cursor, and other AI tools

ClickHouse Python Client

Official Python driver for ClickHouse with SQLAlchemy, Apache Superset, and Pandas integration

chDB — Embedded ClickHouse

In-process ClickHouse engine (like DuckDB for ClickHouse) for serverless local analytics

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