Delv
Official (Vendor)Active· 10d4.3by ClickHouse

ClickHouse

ClickHouse MCP for fast analytical queries. Built by ClickHouse Inc, supports cluster topology discovery.

A
Safety & Trust

Delv Safety Grade: A

Score 83/100 · assessed 2026-04-28

Maintainer95
Permissions65
Supply chain85
Transparency80
Incidents100

ClickHouse MCP is built and maintained by ClickHouse Inc themselves, which gives it excellent pedigree as an official vendor integration. The package is distributed via PyPI with standard installation, and the codebase is open source on GitHub. Security posture is reasonable: it requires database credentials via environment variables and provides both read and write access to your ClickHouse clusters. The permissions scope is broader than read-only analytics tools because it supports full SQL execution including DDL and DML operations. Cluster topology discovery means it can enumerate and connect to multiple nodes. No known security incidents. The main risk is that you're granting Claude direct database access with whatever privileges your credentials carry, so credential scoping and network isolation become critical. Transparency is good with public repo and docs, though changelog detail could be stronger.

Lethal Trifecta (prompt-injection exposure)

ONE OF THREE
Private dataYes
Reads secrets, credentials, private files
Untrusted inputNo
Ingests web pages, PRs, issues, emails
External commsNo
Can send data outbound

Analytical DB; usually private.

Green flags

  • Built and maintained by ClickHouse Inc, official vendor integration
  • Distributed via PyPI with standard pip install
  • Open source on GitHub with public issue tracker
  • Credentials via env vars, not hardcoded
  • Supports read-only mode if credentials are scoped appropriately

Red flags

  • Full SQL execution including DELETE, DROP, and schema modifications
  • Credentials grant whatever DB privileges the user has, no built-in scoping
  • Cluster discovery can enumerate internal topology and multiple nodes
  • Network access to database infrastructure required

Permissions requested

DB readDB writeOutbound networkPrivate networkAccess secrets
Assessed by Delv Editorial using public metadata. Grades are advisory and update as the ecosystem changes. They do not replace your own review of permissions and code before granting an agent access to sensitive systems.

Install

pip install mcp-clickhouse
Env vars needed: CLICKHOUSE_HOSTCLICKHOUSE_USERCLICKHOUSE_PASSWORD

Review

ClickHouse MCP gives Claude direct access to your ClickHouse clusters for analytical queries. It's built by ClickHouse themselves, which means it understands cluster topology and can discover nodes automatically. You point it at a host, pass credentials, and Claude can run SQL queries, inspect schemas, and pull aggregated data without you writing a single line of glue code. I'd reach for this when I'm doing exploratory analysis on large datasets and want to ask questions in plain English rather than writing SQL by hand. The typical workflow: you describe what you want, Claude generates the query, runs it, and explains the results. It's particularly good for ad-hoc reporting where you'd otherwise be context-switching between a chat interface and a database client. The cluster discovery feature is useful if you're running distributed ClickHouse setups, though most single-node users won't notice it. Quirks: it's vendor-official, so it's unlikely to break with ClickHouse updates, but it's also narrowly focused on query execution. Don't expect it to manage migrations or handle schema changes beyond inspection. The environment variables are mandatory, which is sensible for security but means you can't easily switch between multiple ClickHouse instances without reconfiguring. No npm package yet, so installation is a manual clone-and-build process. Who shouldn't bother: if you're not already running ClickHouse, this won't convince you to start. It's a query interface, not a database management tool. If your ClickHouse usage is purely programmatic and you've already got a solid query layer, adding an LLM middleman might be overkill. But if you're doing regular analytical work and want to offload query construction to Claude, it's a clean, purpose-built tool that does exactly what it says.
Verdict

Install this if you're already running ClickHouse and want Claude to handle query construction for exploratory analysis. Skip it if you need database management features or don't have a ClickHouse instance to point it at. It's a narrow tool that does one thing well.

Good at

  • Built by ClickHouse themselves, so it understands vendor-specific features and cluster topology.
  • Turns natural language questions into SQL without you writing queries manually.
  • Cluster discovery works automatically for distributed setups.
  • Tight scope means it does query execution well without feature bloat.

Watch out

  • No npm package yet, so installation requires cloning and building from source.
  • Environment variables are mandatory and stored in plaintext config files.
  • Focused purely on queries, not schema changes or database management tasks.
  • Switching between multiple ClickHouse instances requires manual reconfiguration.

Getting started

1. Clone the repository from GitHub and build it locally since there's no npm package yet. 2. Add the server to your Claude Desktop or Cursor config with CLICKHOUSE_HOST, CLICKHOUSE_USER, and CLICKHOUSE_PASSWORD environment variables. 3. Restart your host application and verify the connection by asking Claude to list your ClickHouse databases or tables. 4. Test a simple aggregation query on a known table to confirm query execution works. 5. Watch out for credential management: the environment variables are plaintext in your config, so keep that file secure.

Works with

Claude DesktopCursor

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