Overview of ClickHouse MCP Server

The ClickHouse MCP Server is a groundbreaking solution that bridges the gap between ClickHouse databases and Large Language Models (LLMs), as well as other AI applications. This server leverages the Model Context Protocol (MCP) to ensure seamless integration, enabling AI models to access and interact with external data sources efficiently.

Key Features

• Resource Listing: The server lists ClickHouse databases and tables as resources, making it easier for AI models to understand the available data landscape.
• Schema Retrieval: Retrieve table schemas effortlessly, allowing AI applications to comprehend the structure of the data they are interacting with.
• Query Execution: Execute SELECT queries on ClickHouse databases, facilitating real-time data retrieval and analysis.
• Secure Communication: The MCP protocol ensures secure and efficient communication between the server and AI applications, safeguarding data integrity and privacy.

Use Cases

1. Data-Driven AI Models: By integrating ClickHouse databases with LLMs, businesses can develop AI models that are more informed and data-driven, leading to better predictions and insights.
2. Real-Time Analytics: Enterprises can leverage the server to perform real-time data analytics, enhancing decision-making processes with up-to-date information.
3. AI-Enhanced Business Operations: With seamless data access, AI applications can automate and optimize various business operations, from customer support to inventory management.

UBOS Platform Integration

The UBOS platform is a full-stack AI Agent Development Platform that complements the capabilities of the ClickHouse MCP Server. UBOS focuses on bringing AI Agents to every business department, orchestrating AI Agents, and connecting them with enterprise data. This synergy allows businesses to build custom AI Agents with their LLM models and Multi-Agent Systems, further enhancing their operational efficiency.

Getting Started

Requirements

• Python 3.10+
• ClickHouse server

Installation

1. Clone the repository:

   git clone https://github.com/ThomAub/clickhouse_mcp_server.git
   cd clickhouse_mcp_server
   

2. Install the required packages:

   uv sync --all-extras
   

3. Set up your ClickHouse connection details in environment variables or update the get_clickhouse_client function in server.py.

Usage

Run the server:

python clickhouse_mcp_server/server.py

The server will start and listen for MCP requests, ready to facilitate seamless integration between ClickHouse and AI applications.

Testing

Run the tests using pytest:

pytest tests/

Contributing

Contributions to the ClickHouse MCP Server are welcome. Developers can submit a Pull Request to enhance the server’s capabilities or address any issues.

License

This project is licensed under the MIT License, ensuring open-source collaboration and development.

In conclusion, the ClickHouse MCP Server is an innovative tool that empowers businesses to harness the full potential of their data through AI integration. By leveraging the UBOS platform, enterprises can further enhance their AI capabilities, driving growth and efficiency across all departments.