Data Dictionary MCP

🚀 Data Dictionary MCP Server

A server that uses the Model Context Protocol (MCP) to coordinate AI agents and convert database tables into Wikipedia-style data dictionaries.

🚀 Quick Start

Prerequisites

• Python 3.9+
• Git
• Dependency management with pip or poetry

Installation

1. Clone the repository:

   git clone https://github.com/jonahkeegan/data-dictionary-mcp.git
   cd data-dictionary-mcp
   

2. Create a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   

3. Install dependencies:

   pip install -r requirements.txt
   

4. Run the application:

   python src/main.py
   

✨ Features

• Multi-format Support: Handle JSON, CSV, and plain text files (more formats coming soon).
• AI-driven Analysis: Generate field descriptions and identify relationships.
• MCP Integration: Coordinate AI agents using the Model Context Protocol.
• Schema Extraction: Extract database schemas from various formats into a unified representation.
• Wikipedia-style Output: Present data dictionaries in a familiar and accessible format.

📚 Documentation

Overview

The Data Dictionary MCP project automates the processing of various database formats to generate comprehensive and easy-to-understand data dictionaries. It leverages AI-driven analysis and description and coordinates AI agents through the Model Context Protocol (MCP) to analyze, describe, and validate database structures.

Project Status

This project is actively under development. Please refer to the Project Roadmap for details.

Project Structure

data-dictionary-mcp/
├── docs/                  # Documentation
├── src/                   # Source code
│   ├── mcp/               # MCP server components
│   ├── analyzers/         # Format analyzers
│   ├── agents/            # Agent coordination
│   └── dictionary/        # Dictionary generation
├── tests/                 # Test suite
├── memory-bank/           # Command-line memory bank
├── .gitignore
├── .clinerules            # Cline rules
├── README.md
└── requirements.txt

Project Roadmap

Phase 1: MCP Server Basics and Format Analyzers

• Implement the basic functions of the MCP server.
• Develop format analyzers for JSON, CSV, and plain text.
• Create a schema extraction system.
• Implement unit tests for core components.

Phase 2: AI Agent Coordination and Field Descriptions

• Implement the agent coordination system.
• Develop field description generation.
• Create task assignment and result aggregation.
• Add integration tests.

Phase 3: Content Validation and Publishing

• Implement content validation.
• Develop Wikipedia-style formatting.
• Create an export function.
• Add end-to-end tests.

Phase 4: User Interface and Deployment

• Develop a web interface.
• Implement a search function.
• Add a user feedback system.
• Create deployment infrastructure.

🤝 Contribution

Contributions are welcome! Please feel free to submit pull requests.

📄 License

This project is open-source and available under the MIT License.