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ClickHouse MCP clickhouse/mcp-clickhouse
Let an assistant inspect ClickHouse tables and query analytical data.
What is ClickHouse MCP? Prepared by LessAI Tools from public project documentation
ClickHouse's official MCP lists databases and tables and executes SQL for analysis or troubleshooting. It requires a reachable ClickHouse instance and database credentials, and runs as a Python package. Queries are read-only by default; writes require explicit configuration and database privileges. Optional chDB support is available for local analysis. Database hosting and runtime costs remain separate.
ClickHouse MCP setup documentation Setup requirements have not been reviewed yet. Check the project’s setup guide.
Setup and usage guide ↗ Based on public documentation; not individually installed and tested here.
ClickHouse MCP use cases List databases and inspect table schemas Run queries in the default read-only mode Optionally use local chDB analysis Official project & documentation The project’s original description Connect ClickHouse to your AI assistants. Alternatives to ClickHouse MCP for similar tasks Matches the main use case first, then shared tasks and stars. Setup methods may differ.
DBHub — Connect an assistant to PostgreSQL, MySQL, SQLite and other SQL databases.Datasette MCP — Give an assistant read-only access to databases in an existing Datasette instance.Neon MCP Server — Explore and manage Neon Postgres databases from your coding assistant.
Sources and ranking × This directory lists AI development plugins with public source code and a clear purpose. Browse by task, then open an introduction to learn what a project does, who it is for, and what you need to get started. It covers selected projects, not every AI plugin.
How do the three plugin types differ? Tool connections (MCP) let AI assistants use external tools such as browsers, code repositories and databases. MCP is the protocol used for these connections.
Reusable skills give a compatible AI assistant instructions and guidance for a particular task.
Editor plugins run inside the software you use to write code, adding AI chat, completions or suggested edits.
How does “Most starred” work? Projects are sorted by their total GitHub stars. Stars indicate interest; they are not downloads, active users or quality scores. A skill pack counts as one project. Daily star growth is not shown without historical records.
What does “Recently updated” mean? It uses the most recent code push, which may not be a new release. The 7-day filter checks that project update time; ranking still uses all-time stars. Each introduction shows when its star count was collected. Failed updates keep the last saved data.
Introductions are based on public project documentation. These projects have not each been installed and tested here. Check the project documentation for setup, compatibility and service costs. Refreshing this list only reads saved data; it does not start collection.
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