SuperSQL MCP Service

@guocjsh

About SuperSQL MCP Service

Super SQL is a Java framework based on advanced generative large models, focusing on transforming database table structures through Retrieval-Augmented Generation (RAG) technology into intelligent conversions from natural language text to SQL queries (Text to SQL). This framework

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "super-sql-mcp-server": {
      "command": "java",
      "args": [
        "-jar",
        "-Dspring.ai.mcp.server.stdio=true",
        "-Dspring.main.web-application-type=none",
        "-Dlogging.pattern.console=",
        "-Dspring.datasource.driver-class-name=com.mysql.cj.jdbc.Driver",
        "-Dspring.datasource.url=jdbc:mysql://localhost:3306/supersql?characterEncoding=utf8&useSSL=false",
        "-Dspring.datasource.username=root",
        "-Dspring.datasource.password=123456",
        "-Dspring.ai.azure.openai.api-key=your_openai_api_key",
        "-Dspring.ai.azure.openai.chat.options.deployment-name=your_chat_model_deployment_name",
        "-Dspring.ai.azure.openai.endpoint=your_openai_endpoint",
        "-Dspring.ai.azure.openai.embedding.options.deployment-name=your_embedding_model_deployment_name",
        "-Dspring.ai.vectorstore.chroma.client.host=http://127.0.0.1",
        "-Dspring.ai.vectorstore.chroma.client.port=8000",
        "-Dspring.ai.vectorstore.chroma.collection-name=super-sql",
        "-Dspring.ai.vectorstore.chroma.initialize-schema=true",
        "D:\\your_jar_file_path\\super-sql-mcp-stdio-1.0.0-M1.jar"
      ],
      "env": {}
    }
  }
}

Tools

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Overview

What is SuperSQL MCP Service?

SuperSQL MCP Service is a Java framework that leverages advanced generative large models to implement NL2SQL (Natural Language to SQL). It uses Retrieval-Augmented Generation (RAG) to train on database table structures, enabling conversion of natural language questions into accurate SQL queries.

How to use SuperSQL MCP Service?

The README does not provide installation, configuration, or invocation instructions. It describes SuperSQL as a Java framework with a concise API design and easy integration into existing projects.

Key features of SuperSQL MCP Service

Generative SQL: automatically converts natural language to precise SQL queries.
RAG training: deep learning on table structures for higher accuracy.
Type-safe and flexible: uses Java generics for compile-time type checking.
Multi-database support: compatible with various mainstream database systems.
Performance optimized: efficient execution with good readability.

Use cases of SuperSQL MCP Service

Rapidly building AI-powered database query interfaces in Java applications.
Simplifying complex database operations for developers via natural language.
Enabling natural language data access for enterprise applications.
Reducing the learning curve for non-technical users to retrieve data.

FAQ from SuperSQL MCP Service

What does SuperSQL MCP Service do?

It converts natural language text into SQL queries using generative large models and RAG technology trained on database schemas.

What runtime environment does it require?

SuperSQL MCP Service is a Java framework, so it requires a Java runtime environment to run and integrate.

Which database systems are supported?

The service is compatible with several mainstream database systems, though specific names are not listed in the README.

How does it ensure SQL generation accuracy?

It uses Retrieval-Augmented Generation (RAG) to train on database table structures, improving the accuracy and relevance of the generated SQL.

What type of users is it intended for?

Developers and users who want to perform complex database operations in Java applications and add AI capabilities to enterprise systems.

Frequently asked questions

What does SuperSQL MCP Service do?

It converts natural language text into SQL queries using generative large models and RAG technology trained on database schemas.

What runtime environment does it require?

SuperSQL MCP Service is a Java framework, so it requires a Java runtime environment to run and integrate.

Which database systems are supported?

The service is compatible with several mainstream database systems, though specific names are not listed in the README.

How does it ensure SQL generation accuracy?

It uses Retrieval-Augmented Generation (RAG) to train on database table structures, improving the accuracy and relevance of the generated SQL.

What type of users is it intended for?

Developers and users who want to perform complex database operations in Java applications and add AI capabilities to enterprise systems.

Comments

Basic information

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