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ClickHouse MCP Server: Real-Time Analytics & AI Reasoning - MCP Implementation

ClickHouse MCP Server: Real-Time Analytics & AI Reasoning

Empower Claude AI with real-time ClickHouse database access – the MCP Server bridges human-like reasoning and high-speed analytics, delivering game-changing insights effortlessly." )

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About ClickHouse MCP Server

What is ClickHouse MCP Server: Real-Time Analytics & AI Reasoning?

This server acts as a bridge between AI models and ClickHouse databases, enabling real-time data crunching and intelligent query execution. Imagine it as your database's turbocharged sidekick, handling everything from simple SELECT statements to complex analytical workloads with a dash of machine learning flair.

How to use ClickHouse MCP Server: Real-Time Analytics & AI Reasoning?

  1. Install via uv or pip like a pro:
  2. uv pip install clickhouse-mcp-server
  3. Configure your environment variables with the precision of a Swiss watchmaker:
  4. export CLICKHOUSE_HOST="your.clickhouse.instance"
  5. Deploy through Claude Desktop with JSON config that's almost artistic in its simplicity.

ClickHouse MCP Server Features

Key Features of ClickHouse MCP Server: Real-Time Analytics & AI Reasoning?

  • Query Juggler: Execute multiple SQL statements in one go with semicolon-separated magic
  • JSON Whisperer: Results automatically translated into developer-friendly JSON format
  • Security Safeguards: Toggle read-only mode like a superhero flipping a switch (SET CLICKHOUSE_READONLY=1)
  • Debugging Nirvana: Pair with MCP Inspector for error detection that feels like having a personal QA analyst

Use cases of ClickHouse MCP Server: Real-Time Analytics & AI Reasoning?

Perfect for scenarios where data needs to be both analyzed and reasoned with:

  • Real-time fraud detection systems that need instant query responses
  • AI training pipelines requiring constant database interaction
  • Dynamic dashboard generators that crave fresh data like a plant craves sunlight
  • Multi-tenant applications where environment-specific configurations are non-negotiable

ClickHouse MCP Server FAQ

FAQ from ClickHouse MCP Server: Real-Time Analytics & AI Reasoning?

Can I use this on Windows?

Absolutely! Just follow the JSON config steps with your %APPDATA% path - no magic required, just standard Windows sorcery.

What happens if I forget the environment variables?

Defaults gracefully step in like polite dinner guests (localhost, root user, etc.), but we recommend customization for production scenarios.

How do I know if the connection worked?

A confirmation message appears like a well-trained service dog - eager to please and provide proof of success.

Content

Clickhouse MCP server

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A Clickhouse database MCP server project.

Installation

You can install the package using uv:

uv pip install clickhouse-mcp-server

Or using pip:

pip install clickhouse-mcp-server

Components

Tools

The server provides two tools:

  • connect_database: Connects to a specific Clickhouse database

    • database parameter: Name of the database to connect to (string)
    • Returns a confirmation message when connection is successful
  • execute_query: Executes Clickhouse queries

    • query parameter: SQL query/queries to execute (string)
    • Returns query results in JSON format
    • Multiple queries can be sent separated by semicolons

Configuration

The server uses the following environment variables:

  • CLICKHOUSE_HOST: Clickhouse server address (default: "localhost")
  • CLICKHOUSE_USER: Clickhouse username (default: "root")
  • CLICKHOUSE_PASSWORD: Clickhouse password (default: "")
  • CLICKHOUSE_DATABASE: Initial database (optional)
  • CLICKHOUSE_READONLY: Read-only mode (set to 1/true to enable, default: false)

Quickstart

Installation

Claude Desktop

MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json

Windows: %APPDATA%/Claude/claude_desktop_config.json

Development/Unpublished Server Configuration
{
  "mcpServers": {
    "clickhouse-mcp-server": {
      "command": "uv",
      "args": [
        "--directory",
        "/Users/burakdirin/Projects/clickhouse-mcp-server",
        "run",
        "clickhouse-mcp-server"
      ],
      "env": {
        "CLICKHOUSE_HOST": "localhost",
        "CLICKHOUSE_USER": "root",
        "CLICKHOUSE_PASSWORD": "password",
        "CLICKHOUSE_DATABASE": "[optional]",
        "CLICKHOUSE_READONLY": "true"
      }
    }
  }
}
Published Server Configuration
{
  "mcpServers": {
    "clickhouse-mcp-server": {
      "command": "uvx",
      "args": [
        "clickhouse-mcp-server"
      ],
      "env": {
        "CLICKHOUSE_HOST": "localhost",
        "CLICKHOUSE_USER": "root",
        "CLICKHOUSE_PASSWORD": "password",
        "CLICKHOUSE_DATABASE": "[optional]",
        "CLICKHOUSE_READONLY": "true"
      }
    }
  }
}

Installing via Smithery

To install Clickhouse Database Integration Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @burakdirin/clickhouse-mcp-server --client claude

Development

Building and Publishing

To prepare the package for distribution:

  1. Sync dependencies and update lockfile:
uv sync
  1. Build package distributions:
uv build

This will create source and wheel distributions in the dist/ directory.

  1. Publish to PyPI:
uv publish

Note: You'll need to set PyPI credentials via environment variables or command flags:

  • Token: --token or UV_PUBLISH_TOKEN
  • Or username/password: --username/UV_PUBLISH_USERNAME and --password/UV_PUBLISH_PASSWORD

Debugging

Since MCP servers run over stdio, debugging can be challenging. For the best debugging experience, we strongly recommend using the MCP Inspector.

You can launch the MCP Inspector via npm with this command:

npx @modelcontextprotocol/inspector uv --directory /Users/burakdirin/Projects/clickhouse-mcp-server run clickhouse-mcp-server

Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.

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