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Data Dictionary MCP Server

@jonahkeegan

代码仓库

基本信息

分类

数据与分析

许可证

MIT license

传输方式

stdio

作者

jonahkeegan

关于 Data Dictionary MCP Server

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 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

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

Data Dictionary MCP Server 工具

工具列表暂未提供

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 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

常见问题

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.

评论

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