mcp-clickhouse-long-running

mcp-clickhouse-long-running

mcp-clickhouse-long-running

Category
访问服务器

README

ClickHouse MCP Server

PyPI - Version

An MCP server for ClickHouse.

<a href="https://glama.ai/mcp/servers/yvjy4csvo1"><img width="380" height="200" src="https://glama.ai/mcp/servers/yvjy4csvo1/badge" alt="mcp-clickhouse MCP server" /></a>

Features

Tools

  • run_select_query

    • Execute SQL queries on your ClickHouse cluster.
    • Input: sql (string): The SQL query to execute.
    • All ClickHouse queries are run with readonly = 1 to ensure they are safe.
  • list_databases

    • List all databases on your ClickHouse cluster.
  • list_tables

    • List all tables in a database.
    • Input: database (string): The name of the database.

Configuration

  1. Open the Claude Desktop configuration file located at:

    • On macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
    • On Windows: %APPDATA%/Claude/claude_desktop_config.json
  2. Add the following:

{
  "mcpServers": {
    "mcp-clickhouse": {
      "command": "uv",
      "args": [
        "run",
        "--with",
        "mcp-clickhouse",
        "--python",
        "3.13",
        "mcp-clickhouse"
      ],
      "env": {
        "CLICKHOUSE_HOST": "<clickhouse-host>",
        "CLICKHOUSE_PORT": "<clickhouse-port>",
        "CLICKHOUSE_USER": "<clickhouse-user>",
        "CLICKHOUSE_PASSWORD": "<clickhouse-password>",
        "CLICKHOUSE_SECURE": "true",
        "CLICKHOUSE_VERIFY": "true",
        "CLICKHOUSE_CONNECT_TIMEOUT": "1800",
        "CLICKHOUSE_SEND_RECEIVE_TIMEOUT": "1800"
      }
    }
  }
}

Update the environment variables to point to your own ClickHouse service.

Or, if you'd like to try it out with the ClickHouse SQL Playground, you can use the following config:

{
  "mcpServers": {
    "mcp-clickhouse": {
      "command": "uv",
      "args": [
        "run",
        "--with",
        "mcp-clickhouse",
        "--python",
        "3.13",
        "mcp-clickhouse"
      ],
      "env": {
        "CLICKHOUSE_HOST": "sql-clickhouse.clickhouse.com",
        "CLICKHOUSE_PORT": "8443",
        "CLICKHOUSE_USER": "demo",
        "CLICKHOUSE_PASSWORD": "",
        "CLICKHOUSE_SECURE": "true",
        "CLICKHOUSE_VERIFY": "true",
        "CLICKHOUSE_CONNECT_TIMEOUT": "1800",
        "CLICKHOUSE_SEND_RECEIVE_TIMEOUT": "1800"
      }
    }
  }
}
  1. Locate the command entry for uv and replace it with the absolute path to the uv executable. This ensures that the correct version of uv is used when starting the server. On a mac, you can find this path using which uv.

  2. Restart Claude Desktop to apply the changes.

Development

  1. In test-services directory run docker compose up -d to start the ClickHouse cluster.

  2. Add the following variables to a .env file in the root of the repository.

Note: The use of the default user in this context is intended solely for local development purposes.

CLICKHOUSE_HOST=localhost
CLICKHOUSE_PORT=8123
CLICKHOUSE_USER=default
CLICKHOUSE_PASSWORD=clickhouse
  1. Run uv sync to install the dependencies. To install uv follow the instructions here. Then do source .venv/bin/activate.

  2. For easy testing, you can run mcp dev mcp_clickhouse/mcp_server.py to start the MCP server.

Environment Variables

The following environment variables are used to configure the ClickHouse connection:

Required Variables

  • CLICKHOUSE_HOST: The hostname of your ClickHouse server
  • CLICKHOUSE_USER: The username for authentication
  • CLICKHOUSE_PASSWORD: The password for authentication

[!CAUTION] It is important to treat your MCP database user as you would any external client connecting to your database, granting only the minimum necessary privileges required for its operation. The use of default or administrative users should be strictly avoided at all times.

Optional Variables

  • CLICKHOUSE_PORT: The port number of your ClickHouse server
    • Default: 8443 if HTTPS is enabled, 8123 if disabled
    • Usually doesn't need to be set unless using a non-standard port
  • CLICKHOUSE_SECURE: Enable/disable HTTPS connection
    • Default: "true"
    • Set to "false" for non-secure connections
  • CLICKHOUSE_VERIFY: Enable/disable SSL certificate verification
    • Default: "true"
    • Set to "false" to disable certificate verification (not recommended for production)
  • CLICKHOUSE_CONNECT_TIMEOUT: Connection timeout in seconds
    • Default: "1800"
    • Increase this value if you experience connection timeouts
  • CLICKHOUSE_SEND_RECEIVE_TIMEOUT: Send/receive timeout in seconds
    • Default: "1800"
    • Increase this value for long-running queries
  • CLICKHOUSE_DATABASE: Default database to use
    • Default: None (uses server default)
    • Set this to automatically connect to a specific database

Example Configurations

For local development with Docker:

# Required variables
CLICKHOUSE_HOST=localhost
CLICKHOUSE_USER=default
CLICKHOUSE_PASSWORD=clickhouse

# Optional: Override defaults for local development
CLICKHOUSE_SECURE=false  # Uses port 8123 automatically
CLICKHOUSE_VERIFY=false

For ClickHouse Cloud:

# Required variables
CLICKHOUSE_HOST=your-instance.clickhouse.cloud
CLICKHOUSE_USER=default
CLICKHOUSE_PASSWORD=your-password

# Optional: These use secure defaults
# CLICKHOUSE_SECURE=true  # Uses port 8443 automatically
# CLICKHOUSE_DATABASE=your_database

For ClickHouse SQL Playground:

CLICKHOUSE_HOST=sql-clickhouse.clickhouse.com
CLICKHOUSE_USER=demo
CLICKHOUSE_PASSWORD=
# Uses secure defaults (HTTPS on port 8443)

You can set these variables in your environment, in a .env file, or in the Claude Desktop configuration:

{
  "mcpServers": {
    "mcp-clickhouse": {
      "command": "uv",
      "args": [
        "run",
        "--with",
        "mcp-clickhouse",
        "--python",
        "3.13",
        "mcp-clickhouse"
      ],
      "env": {
        "CLICKHOUSE_HOST": "<clickhouse-host>",
        "CLICKHOUSE_USER": "<clickhouse-user>",
        "CLICKHOUSE_PASSWORD": "<clickhouse-password>",
        "CLICKHOUSE_DATABASE": "<optional-database>"
      }
    }
  }
}

Running tests

uv sync --all-extras --dev # install dev dependencies
uv run ruff check . # run linting

docker compose up -d test_services # start ClickHouse
uv run pytest tests

YouTube Overview

YouTube

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选