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Clickhouse MCP Server
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Clickhouse MCP Server

This project implements a ClickHouse MCP server for seamless integration of the ClickHouse database with AI applications such as large language models (LLMs), supporting functions such as querying databases and obtaining table structures.
DatabaseArtificial intelligence chatbots#Database integration#AI connection#MCP protocol.Python
2.5 points
8.5K
Open Site

Overview

Content Details

Alternatives

What is ClickHouse MCP Server?

ClickHouse MCP Server is a middleware service that acts as a bridge between the ClickHouse database and AI applications (such as large language models). Through the standardized MCP protocol, AI applications can easily access and query data in the ClickHouse database.

How to use ClickHouse MCP Server?

After installation and configuration, AI applications can communicate with the server through the MCP protocol to perform operations such as database queries and obtaining table structures without directly connecting to the database.

Use cases

Suitable for various application scenarios that require combining structured database data with AI capabilities, such as data analysis assistants, intelligent report generation, and data-driven dialogue systems.

Main features

Database resource discovery
Automatically discover and list all database and table resources in ClickHouse
Table structure query
Get detailed structure information of any data table, including field names, types, etc.
Data query execution
Support executing SELECT queries and returning structured results
Secure communication
Use the MCP protocol to ensure the security and efficiency of data transmission
Advantages
Simplify the integration of AI applications and databases
Provide a standardized data access interface
Avoid the security risks of AI applications directly connecting to databases
Optimize data transmission efficiency
Limitations
Currently only supports the ClickHouse database
The functions are relatively basic and do not support complex transactions
Requires additional maintenance of server components

How to use

Installation preparation
Ensure that Python 3.10+ and the ClickHouse server are installed
Clone the repository
Get the project source code
Install dependencies
Install all necessary Python packages
Configure the connection
Set the ClickHouse connection parameters
Start the server
Run the MCP server

Usage examples

Data analysis assistant
Obtain the sales data analysis results in the database through natural language queries
Intelligent report generation
Automatically generate a daily report containing the latest business indicators

Frequently asked questions

Which databases does the MCP server support?
How to ensure communication security?
Does it support write operations?
How about the performance?

Related resources

ClickHouse official documentation
The official documentation of the ClickHouse database
MCP protocol specification
The official specification of the Model Context Protocol
GitHub repository
The project source code

Installation

Copy the following command to your Client for configuration
Note: Your key is sensitive information, do not share it with anyone.

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