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Data Dictionary MCP Server

@jonahkeegan

リポジトリ

基本情報

カテゴリ

データと分析

ライセンス

MIT license

トランスポート

stdio

作者

jonahkeegan

Data Dictionary MCP Server について

A Model Context Protocol (MCP) server that coordinates AI agents to transform database tables into Wikipedia-style data dictionaries.

#data-dictionary#mcp#ai-agents

Data Dictionary 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": {
    "data-dictionary-mcp": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        "venv"
      ]
    }
  }
}

Data Dictionary 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 Data Dictionary MCP?

Data Dictionary MCP is a Model Context Protocol server that automates the conversion of database tables into Wikipedia-style data dictionaries. It uses AI agents coordinated via MCP to analyze, describe, and verify database structures.

How to use Data Dictionary MCP?

Clone the repository, create a Python 3.9+ virtual environment, install dependencies from requirements.txt, then run python src/main.py.

Key features of Data Dictionary MCP

  • Multi-Format Support: JSON, CSV, and Plain Text files
  • AI-Powered Analysis: generate field descriptions and relationships
  • MCP Integration: coordinate AI agents via the protocol
  • Schema Extraction: unify schemas from various formats
  • Wikipedia-Style Output: familiar, accessible presentation format

Use cases of Data Dictionary MCP

  • Create comprehensive data dictionaries from database schemas
  • Automatically describe fields and identify relationships with AI
  • Convert JSON, CSV, and plain text into structured dictionaries
  • Leverage AI agents to verify and improve dictionary accuracy

よくある質問

1

What file formats are supported?

JSON, CSV, and Plain Text are supported; more formats are planned.

2

What are the prerequisites?

Python 3.9+, Git, and pip or poetry for dependency management.

3

Is this project production-ready?

No, it is in active development. See the Project Roadmap for details.

4

How can I contribute?

Contributions are welcome via Pull Requests.

5

What license does this project use?

MIT License.

コメント

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