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clickhouse-mcp-server

by burakdirin
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Python
Hybrid

Clickhouse MCP server

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

Related MCP server: 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

{
  "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"
      }
    }
  }
}
{
  "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.

Available Tools

2 tools
connect_databaseC

Connect to a specific ClickHouse database

ParametersJSON Schema
NameRequiredDescriptionDefault
databaseYes

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It only says 'Connect', omitting details about side effects, authentication requirements, or state changes (e.g., establishing a session).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence with no unnecessary words. It is effectively concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's role as a connection setter, the description lacks information on prerequisites, return values, or how it interacts with 'execute_query'. It is incomplete for operational context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% and the description adds no additional meaning beyond the parameter name 'database'. It does not explain valid values or expected format.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Connect to a specific ClickHouse database', using a specific verb and resource. It effectively distinguishes from the sibling tool 'execute_query' which presumably runs queries.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus the sibling 'execute_query' or any prerequisites. The description merely states functionality without usage context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

execute_queryC

Execute ClickHouse queries

ParametersJSON Schema
NameRequiredDescriptionDefault
queryYes

TDQS

C2.4/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided. The description does not disclose whether queries are read-only, safe, or have side effects. Important behavioral details like result handling or error behavior are missing.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence, which is concise but at the expense of necessary detail for a query execution tool. It is too minimal to be considered well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With one parameter and no output schema, the description fails to explain what the tool returns or if it just executes. Lacks context about execution environment and limitations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, and the description adds no information about the 'query' parameter beyond its name. Does not specify expected format (e.g., SQL dialect) or constraints.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action (Execute) and resource (ClickHouse queries). It distinguishes from the sibling tool connect_database, which implies connection setup vs query execution.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives. Does not mention prerequisites like a prior connection or whether it is for read or write operations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

B3.1/5.0
Disambiguation5/5

The two tools have clearly distinct purposes: one for establishing a database connection, the other for executing queries. There is no overlap or ambiguity.

Naming Consistency5/5

Both tool names follow a consistent verb_noun pattern (connect_database, execute_query), making them predictable and easy to understand.

Tool Count4/5

With only 2 tools, the set is minimal but still covers the essential operations for a database query server. It is slightly thin but reasonable for a focused scope.

Completeness3/5

The tools cover connection and query execution, but lack disconnect, schema inspection, or database management operations. This leaves notable gaps for a full database interaction workflow.

Maintenance

ActivityInactive
ResponsivenessSyncing

Resources

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