machbase-mcp-server

machbase/machbase-mcp-server

3.3

If you are the rightful owner of machbase-mcp-server and would like to certify it and/or have it hosted online, please leave a comment on the right or send an email to henry@mcphub.com.

This project is an MCP-based server that facilitates natural language database operations between Claude Desktop and Machbase Neo.

Diagram

Overview (Version 0.4.0)

블로그 읽기 : 클로드 MCP를 Machbase Neo에 연동하고, AI스럽게 사용해보기

This project is an MCP (Model Context Protocol) based server that enables natural language-based database operations through integration between Claude Desktop and Machbase Neo.

When users request database operations in natural language through Claude Desktop's MCP connection, the MCP server converts these requests into Machbase Neo commands and executes them.

Youtube Link

Key Features

  • Machbase Neo Official Documentation Search & AI-powered Explanations
    • Claude directly searches Machbase documentation to provide accurate information
  • Real-time Database Integration
    • Table creation, data manipulation, complex query execution
    • Natural language → SQL conversion through Claude
  • Time Series Data Analysis & Querying
    • Analysis of IoT sensor data, log data, and other time series data
  • Native Claude Desktop Integration
    • No additional API keys required, leverages Claude Desktop's built-in capabilities

How It Works

StepComponentRoleCommunication
1UserInput natural language requestChat interface
2Claude DesktopParse request & call MCP toolsMCP Protocol
3MCP ServerGenerate SQL & connect to MachbaseHTTP/REST API
4Machbase NeoExecute database operationsSQL queries

Data Flow:

User Request → Claude Desktop → MCP Server → Machbase Neo
↑                                                      ↓
Response ← Claude Interpretation ← MCP Response ← Query Results

Installation

Quick Setup

Windows
  1. Install Claude Desktop (if you don't have it yet)

  2. Download project from Git

    git clone https://github.com/your-org/Machbase_MCP_Server.git
    cd Machbase_MCP_Server
    
    
  3. Run automatic installation

    MCP_Install.bat
    
MacOS
  1. Download project from Git
    git clone https://github.com/your-org/Machbase_MCP_Server.git
    cd Machbase_MCP_Server
    
    
  2. Run automatic installation
    ./MCP_Install_mac.sh
     
    

After installation: Restart Claude Desktop and test with "Show me the Machbase table list!"

Manual Setup

For manual installation or if errors occur during the above installation process:

  1. Clone Repository
    git clone https://github.com/your-org/Machbase_MCP_Server.git
    cd Machbase_MCP_Server
    
    
  2. Python Environment Setup
    # Using Conda
    conda create -n mcp python=3.11
    conda activate mcp
    
    # Using venv
    python -m venv mcp-env
    source mcp-env/bin/activate  # Linux/macOS
    # mcp-env\Scripts\activate   # Windows
    
    
  3. Install Dependencies
    pip install -r requirements.txt
    
    
  4. Claude Desktop and MCP Server Configuration
    # Create C:/Users/Username/AppData/Roaming/Claude/claude_desktop_config.json
    # Machbase.py to C:/Users/Username/AppData/Roaming/Claude/
    
    {
        "mcpServers": {
          "machbase": {
            "command": "C:/Users/Username/anaconda3/envs/mcp/python.exe",
            "args": ["C:/Users/Username/AppData/Roaming/Claude/Machbase.py"],
            "env": {
              "MACHBASE_HOST": "localhost",
              "MACHBASE_PORT": "5654"
              }
          }
       }
    }
        
    

Usage Examples

You can make natural language requests in Claude Desktop like these:

"Create a table for temperature logs"
"Insert today's temperature: 28.4°C at 9am"
"Show me the latest 10 rows from temperature_log"
"Search the Machbase documentation for 'data insertion'"
"Drop the table named old_sensor_data"
"Show average temperature over the past 3 days"
"What tables exist in my Machbase database?"
"List all columns in sensor_data"
"Generate a trend report for device_001"

Machbase MCP Server Evaluation Score

Update DateVersionScoreAverage Response TimeOverall Evaluation
2025-08-28v0.2.096 / 10022 secondThe quality of responses has improved compared to previous versions;
however, performance regarding TQL-related questions still appears to be less than perfect.
2025-09-03v0.3.099 / 10061.5 secondThe response time is much longer, but the explanation is far more accurate and detailed than the previous version.
2025-09-09v0.4.0141 / 15045.29 secondThe speed has improved compared to before, but the script and TQL parts are still somewhat lacking