mcp-clickhouse

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Overview

The mcp-clickhouse server is a Model Context Protocol (MCP) server that enables AI assistants and agents to interact directly with ClickHouse, the high-performance, column-oriented analytical database. It allows AI-driven workflows to query large datasets, inspect schemas, and analyze analytical workloads without switching tools or embedding ClickHouse-specific client logic.

This server is especially useful for analytics, observability, log analysis, and data exploration workflows where fast, read-heavy queries and large-scale datasets are common.

Transport

stdio

Tools

  • list_databases
  • list_tables
  • run_select_query

Key Capabilities

  • High-performance analytics — Run fast analytical queries on large datasets using ClickHouse’s columnar engine.
  • Schema introspection — Explore databases, tables, columns, and data types programmatically.
  • Log and event analysis — Query time-series, log, or event data efficiently.
  • Operational insight — Inspect system tables and metadata for performance or usage analysis.
  • AI-assisted exploration — Enable assistants to summarize trends, anomalies, and query results.

How It Works

The mcp-clickhouse server runs as a local or containerized MCP service and connects to a ClickHouse instance using configured connection details such as host, port, database, and credentials. AI clients communicate with the server over the MCP protocol to request analytical context as part of broader reasoning workflows.

The server mediates access to ClickHouse’s SQL interface, handling query execution and result normalization before returning structured outputs that AI assistants can reason over directly. This abstraction allows AI workflows to focus on analysis and insight rather than database connectivity or driver management.

By exposing ClickHouse through MCP, the server enables AI-driven workflows such as exploratory analysis, dashboard support, anomaly investigation, and large-scale data summarization — all through natural language and automated reasoning within a single environment.