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SQL Server Table Assistant - Modal Context Protocol MCP Server

@hblaDCOM

リポジトリ

基本情報

カテゴリ

AI とエージェント

ライセンス

MIT

トランスポート

stdio

作者

hblaDCOM

SQL Server Table Assistant - Modal Context Protocol MCP Server について

SQL Server Agent tool (with MCP)

SQL Server Table Assistant - Modal Context Protocol MCP Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

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

SQL Server Table Assistant - Modal Context Protocol MCP Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

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.

よくある質問

1

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.

2

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.

3

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.

4

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.

5

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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