How ClickHouse Uses Claude

We have relaunched clickhouse.com/docs on Mintlify, with a redesigned search and Ask AI experience, a docs MCP server, simpler navigation, an interactive API playground, and expanded localization — built for both human readers and the coding agents

A behind-the-scenes look at hdx-evals, the open-source framework we built to benchmark the ClickStack MCP server against a raw SQL baseline using deterministic synthetic incidents, sandboxed Claude agents, and blind LLM grading — and why the MCP scored hi

Search and uncover technology trends across 10 billion GitHub events in real time.

This post shows a lightweight metrics layer for ClickHouse using MooseStack, an open source developer agent harness for ClickHouse.

How to remain competitive in the AI era of software engineering

Retention limits, sampling, and metric roll-ups aren't observability best practices - they're workarounds for storage systems that can't handle full-fidelity data, and they're becoming a hard blocker for AI-driven workflows.

A Solutions Architect’s experience building a retail analytics platform with AI agents, real-time dashboards, and full observability on the ClickHouse data platform

otel.fyi is a search-first site for OpenTelemetry Collector docs, making it easy to quickly find and understand configuration for receivers, processors, exporters, and extensions without digging through scattered documentation.

We use clickhousectl to spin up multiple ClickHouse versions side by side and benchmark two recent performance improvements.

ClickHouse 26.5 is here! In this release, we have a record number of performance optimizations, a new `filesystem` table function for querying your local file system with SQL, and more!

What started as an internal sizing tool for ClickStack became ClickCannon: an open-source framework for stress-testing ClickHouse with realistic data and user workloads.

We've had decades to learn what it means to design software and hardware for humans. How do we build experiences where the primary user may now be an LLM?

We've released @clickhouse/rowbinary a Node.js reader and writer for ClickHouse's RowBinary formats. You can import it and call its generic parser like any other library. But it also ships as an Agent Skill: point a coding agent at the bundled `SKILL.md`

Welcome to the July 2026 ClickHouse newsletter, which will round up what’s happened in real-time data warehouses over the last month.

This article details the transformation of ClickHouse's internal data warehouse from a traditional BI-first approach to an AI-first model, significantly enhancing user accessibility to analytics.

The article discusses how weather data can be derived from airplane telemetry using ADS-B data.

The article discusses the rising costs associated with observability in software engineering and proposes a shift towards open, cost-efficient architectures.

The article explores the potential of Large Language Models (LLMs) to replace Site Reliability Engineers (SREs) in performing root cause analysis (RCA) for production issues.

The article discusses the importance of LLM observability using ClickStack, OpenTelemetry, and MCP, highlighting how to instrument LibreChat for enhanced insights into AI-driven applications.

The article explores the analysis of Wimbledon tennis data using ClickHouse, detailing the unique scoring system of tennis and how to implement a function to compute points needed to win a game.

This article discusses how to build an agentic application using ClickHouse MCP Server and CopilotKit, focusing on creating a customizable analytics dashboard for the UK real estate market.

The article discusses the integration of ClickHouse with the Model Context Protocol (MCP), highlighting its benefits for connecting third-party services to large language models (LLMs).

The article introduces AgentHouse, an interactive demo environment that integrates ClickHouse's real-time analytics with Anthropic's large language model, Claude Sonnet.

This article discusses the development of a Retrieval-Augmented Generation (RAG) pipeline for Google Analytics using ClickHouse and Amazon Bedrock.

This article is the second part of a series on vector search using ClickHouse, focusing on practical implementations and use cases.