mcp_mysql_local_llm

RajiReddy-A/mcp_mysql_local_llm

3.2

If you are the rightful owner of mcp_mysql_local_llm 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.

The Model Context Protocol (MCP) server facilitates communication between local or remote databases and language models, enabling seamless data querying and processing.

Tools
1
Resources
0
Prompts
0

Query MySQL via MCP & Local LLM

This guide shows how to:

  • Run the MySQL MCP server (@executeautomation/database-server) on Windows
  • Install and use the MCP client CLI (llm from mcp-client-cli) to talk to that server
  • Use a local Ollama model or OpenAI compatible API

All commands below are for Windows Command Prompt (cmd.exe).

Prerequisites

  • Python 3.12+ (64‑bit) installed and on PATH
  • pipx installed
  • Node.js 20+ installed (needed for npx to run the MCP server)
  • MySQL running locally with a database treedb and a user you can use
  • (Optional) Ollama installed if you want a local model (eg: qwen3:8b)

Verify basics

python --version
node --version
npm --version

Install pipx (if you don’t have it)

python -m pip install --user pipx
pipx ensurepath

Close & reopen your terminal so %USERPROFILE%\.local\bin is on PATH.

Start the MySQL MCP server

Open a dedicated Command Prompt and run (leave it open):

npx -y @executeautomation/database-server --mysql --host localhost --database treedb --port 3306 --user colab --password colab123

You should see logs like "MySQL connection established successfully" and "Starting MCP server…".

Install the MCP Client CLI (llm)

Install with pipx:

pipx install mcp-client-cli==1.0.4 --python 3.12
pip install -r requirements.txt  # (or) pipx inject mcp-client-cli -r requirements.txt

Check that llm is on PATH:

llm --help

If llm is not found, ensure %USERPROFILE%\.local\bin is in your User PATH, then open a new terminal.

To see what got installed into the pipx venv:

pipx list
pipx runpip mcp-client-cli show langgraph
pipx runpip mcp-client-cli show langgraph-prebuilt
pipx runpip mcp-client-cli show langgraph-sdk
pipx runpip mcp-client-cli show langgraph-checkpoint

Use a local Ollama model

Install and start Ollama, then pull a model (example: Qwen 3 8B):

ollama run qwen3:8b

Update ~/.llm/config.json

 {
     "systemPrompt": "You are a helpful assistant that can also use MCP tools.",
     "llm": {
         "provider": "openai",
         "model": "qwen3:8b",
         "base_url": "http://localhost:11434/v1",
         "api_key": "ollama",
         "temperature": 0.2
     },
     "mcpServers": {
         "mysql": {
             "command": "npx",
             "args": [
                 "-y",
                 "@executeautomation/database-server",
                 "--mysql",
                 "--host", "localhost",
                 "--database", "treedb",
                 "--port", "3306",
                 "--user", "colab",
                 "--password", "colab123"
             ]
         }
     }
 }

(Optional) Use OPENAI API

Replace llm section in above json with this

 "llm": {
     "provider": "openai",
     "model": "gpt-4.1-mini",
     "api_key": "YOUR_OPENAI_API_KEY",
     "temperature": 0.2
 }

Sample DB Query

llm "Show the first 5 rows from the customers table in treedb."

Override config.json params

llm --model qwen3:14b "Show the first 5 rows from the customers table in treedb."