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clickhouse

该 Skill 面向希望了解或开始使用 ClickHouse 的用户,概述 ClickHouse、Cloud、Postgres、ClickStack、chDB、ClickPipes 等产品,并提供通过 clickhousectl 安装 CLI、启动本地服务、创建云服务及执行 SQL 的入门命令,同时指向文档、API 目录、Agent Skills 和 MCP 资料。

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热度 0.00
最近更新 2026-10-19 07:49:15
分类:知识依赖:纯提示词应用场景:概念解释 / 教学辅导 / 工作流

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add clickhouse.com/clickhouse
Metadata
name
clickhouse
description
Get started with ClickHouse. What it is, and how to install, run, and query ClickHouse locally and in ClickHouse Cloud using the clickhousectl CLI. Use this when a user wants to understand ClickHouse or start building with it.
license
Apache-2.0
metadata
{"author":"ClickHouse Inc","version":"0.1.0"}

ClickHouse

ClickHouse is an open-source, column-oriented database for real-time analytics at scale, built to run aggregations over billions of rows in milliseconds. It powers observability platforms, product and web analytics, data warehousing, time-series and ML workloads, and increasingly the data layer behind AI agents.

Products

  • ClickHouse: the open-source column-oriented database for real-time analytics.
  • ClickHouse Cloud: the fully managed service for both ClickHouse and Postgres. Handles scaling, backups, upgrades, security, and enterprise operations.
  • Postgres: fully managed Postgres in ClickHouse Cloud.
  • ClickStack: open-source observability stack built on OpenTelemetry, ClickHouse, and HyperDX for logs, metrics, and traces. Also available as a managed service in ClickHouse Cloud.
  • chDB: in-process ClickHouse: an embeddable SQL engine you can run inside Python and other languages with no server.
  • ClickPipes: managed, continuous data ingestion into ClickHouse Cloud from Kafka, object storage, Postgres, and more.
  • Langfuse: open-source LLM engineering and observability platform, backed by ClickHouse.
  • clickhousectl: the official CLI for ClickHouse, for both local and Cloud. Supports ClickHouse, Postgres and ClickPipes.
  • Agentic data stack: ClickHouse + LibreChat + the ClickHouse MCP server + Langfuse for building AI-native data applications.

Quick start (local)

# Install the clickhousectl CLI
curl -fsSL https://clickhouse.com/cli | sh

# Install the latest ClickHouse and set it as the default
clickhousectl local use latest

# Start a local server (named "default")
clickhousectl local server start

# Run a query against it
clickhousectl local client -q "SELECT 'Hello, world!'"

These steps install the CLI, install ClickHouse, start a local server, and run a query. clickhousectl can install any version of ClickHouse and run multiple named local servers side by side. It can also provision a local Postgres instance, so you can develop against ClickHouse and Postgres together as a unified data stack.

ClickHouse Cloud

ClickHouse Cloud is the managed service for ClickHouse and Postgres. It handles scaling, backups, upgrades, security, and enterprise operations for both, so you don't run any infrastructure yourself.

# Create an account (opens your browser)
clickhousectl cloud auth signup

# Authenticate the CLI. The default OAuth login is read-only;
# creating and managing resources requires an API key.
clickhousectl cloud auth login --api-key <key> --api-secret <secret>

# Create a managed ClickHouse service
clickhousectl cloud service create --name <name>

# Create a managed Postgres service (beta)
clickhousectl cloud postgres create --name <name>

Run SQL against a Cloud service over HTTP with clickhousectl cloud service query --name <name> -q "<sql>".

Documentation

Full documentation: https://clickhouse.com/docs

APIs

Public APIs (including the ClickHouse Cloud API and its OpenAPI spec) are listed in the API catalog (RFC 9727): https://clickhouse.com/.well-known/api-catalog

Agent skills

Install the official ClickHouse agent skills into your coding agent (Claude Code, Cursor, Codex, and more). These teach your agent how to use ClickHouse and the CLI:

clickhousectl skills

Browse the full skill library at https://github.com/ClickHouse/agent-skills

ClickHouse MCP server

Connect ClickHouse to AI assistants via the Model Context Protocol: run queries, list databases, and explore tables from your agent.

Docs: https://clickhouse.com/docs/guides/use-cases/ai-ml/MCP