SQL Server Table Assistant - Modal Context Protocol MCP Server

@hblaDCOM

代码仓库

基本信息

分类

AI 与智能体

许可证

MIT

传输方式

stdio

作者

hblaDCOM

关于 SQL Server Table Assistant - Modal Context Protocol MCP Server

SQL Server Agent tool (with MCP)

SQL Server Table Assistant - Modal Context Protocol MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "sql-server-table-assistant": {
      "command": "python",
      "args": [
        "mcp-ssms-client.py"
      ]
    }
  }
}

SQL Server Table Assistant - Modal Context Protocol MCP Server 工具

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当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is SQL Server Table Assistant - Modal Context Protocol?

SQL Server Table Assistant - Modal Context Protocol is an application that lets you interact with a specific SQL Server table using natural language. It uses the Modal Context Protocol as a communication layer between LLMs and your data source, and is based on the original mcp-sql-server-natural-lang repository with modifications for single‑table access.

How to use SQL Server Table Assistant - Modal Context Protocol?

Clone the repository, install dependencies with pip install -r requirements.txt, and create a .env file with Azure OpenAI credentials and SQL Server connection details. Then run python mcp-ssms-client.py and type your requests in plain English. Special commands like /diagnose, /refresh_schema, and /history are available.

Key features of SQL Server Table Assistant - Modal Context Protocol

Chat with a SQL Server table using plain English.
Iteratively refine SQL queries with user feedback.
View results in well‑formatted tables.
Automatic query history and logging.
Perform no‑code CRUD operations via conversation.
Secure single‑table access with token optimization.

Use cases of SQL Server Table Assistant - Modal Context Protocol

Non‑technical users querying a database table in natural language.
Rapidly prototyping and debugging SQL queries through interactive feedback.
Performing data analysis on a specific table without writing SQL.
Logging all query interactions for compliance or training purposes.
Teaching SQL concepts by reviewing generated queries and explanations.

常见问题

How is this different from the full MCP SQL Server natural language project?

This version focuses on a single table, enhancing security and simplifying permissions. Access is limited to one table rather than the entire database, reducing risk and simplifying credential setup.

What are the prerequisites to run the assistant?

You need Python 3.12+, a valid Azure OpenAI deployment with API access, a SQL Server instance with a target table, and limited user credentials that only have access to that table.

How does token optimization work?

Smart schema summarization, response caching, minimal prompt design, conversation management, dedicated system prompts, selective result trimming, and conservative max_tokens settings minimize API usage and help avoid rate limits.

What should I do if I have connection issues?

Verify your server name/IP is correct, ensure SQL Server accepts remote connections and firewall rules allow traffic, check that the ODBC driver specified in the `.env` file is installed, and test connectivity with tools like SSMS or sqlcmd.

Are INSERT/UPDATE/DELETE operations safe?

Yes. All operations are shown for user approval before execution, and write tests use transactions with rollback. Structured query generation also helps prevent SQL injection.

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