Skill Detail

Query ClickHouse analytics safely from MCP clients

Use ClickHouse's official MCP server when an assistant needs schema-aware, reviewable analytics access to ClickHouse through bounded tools instead of ad hoc database credentials.

Data Extraction & TransformationMCP
Data Extraction & Transformation MCP Security Reviewed
⭐ 801 GitHub stars
INSTALL WITH ANY AGENT
npx skills add agentskillexchange/skills --skill query-clickhouse-analytics-safely-from-mcp-clients Copy
Works best when you want a reusable capability, not another fragile one-off prompt.
At a glance
Tools required
Python runtime or package runner, mcp-clickhouse package, ClickHouse credentials, MCP-capable client
Install & setup
Install the official mcp-clickhouse package, configure ClickHouse connection environment variables, keep write access disabled by default, and register the server with the intended MCP client.
Author
ClickHouse
Publisher
Official Open Source
Last updated
Jun 12, 2026
Quick brief

ClickHouse mcp-clickhouse is the official MCP server for connecting AI assistants to ClickHouse databases. It gives an agent a narrow tool surface for analytics work: list databases, inspect tables, fetch table metadata, and run SQL queries against a ClickHouse cluster with read-only mode enabled by default unless write access is explicitly configured.

How it works

What this skill actually does

Use this skill when a user wants an MCP-capable assistant to answer analytics questions, inspect schemas, prepare read-only SQL, or summarize operational data from ClickHouse without handing the assistant a raw database shell. The operator should configure ClickHouse connection settings, expose only the intended cluster or database scope, keep write access disabled unless there is a deliberate approval path, and review generated SQL before using results in reports, incidents, dashboards, or tickets.

This is not a generic ClickHouse listing or a broad database framework entry. The scope boundary is the official MCP bridge and its documented tools: configure credentials, connect the MCP server to an agent client, use schema/list/query tools for analytics, and keep permissions bounded. If the task is database migration, application development, or manual BI exploration, use the relevant database tooling directly instead.

Inputs and prerequisites: Python environment or package runner, the mcp-clickhouse package, ClickHouse host and credentials, MCP client configuration, and explicit policy for read-only versus write-enabled queries.

Setup notes: Install mcp-clickhouse from the upstream package instructions, set the required ClickHouse environment variables, keep CLICKHOUSE_ALLOW_WRITE_ACCESS=false by default, and register the server with the MCP client that will run the analytics workflow.

Source and verification boundary: use https://github.com/ClickHouse/mcp-clickhouse as the canonical reference before running the workflow; keep MCP tool calls, generated SQL, credentials scope, and query outputs reviewable against that upstream source.