# Data Dictionary MCP

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

## Overview

The Data Dictionary MCP project automates the conversion of various database formats into comprehensive, human-readable data dictionaries using AI-powered analysis and description. It leverages the Model Context Protocol (MCP) to coordinate AI agents for analyzing, describing, and verifying database structures.

## Features

- **Multi-Format Support**: Process JSON, CSV, and Plain Text files (with more formats planned)
- **AI-Powered 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, accessible format

## Project Status

This project is in active development. See the [Project Roadmap](#project-roadmap) for details.

## Getting Started

### Prerequisites

- Python 3.9+
- Git
- pip or poetry for dependency management

### Installation

1. Clone the repository:
   ```bash
   git clone https://github.com/jonahkeegan/data-dictionary-mcp.git
   cd data-dictionary-mcp
   ```

2. Create a virtual environment:
   ```bash
   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   ```

3. Install dependencies:
   ```bash
   pip install -r requirements.txt
   ```

4. Run the application:
   ```bash
   python src/main.py
   ```

## 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/           # Cline memory bank
├── .gitignore
├── .clinerules            # Cline rules
├── README.md
└── requirements.txt
```

## Project Roadmap

### Milestone 1: MCP Server Foundation and Format Analyzers
- Implement MCP server with basic tool definitions
- Develop format analyzers for JSON, CSV, and Plain Text
- Create schema extraction system
- Implement unit tests for core components

### Milestone 2: AI Agent Coordination and Field Description
- Implement agent coordination system
- Develop field description generation
- Create task distribution and result aggregation
- Add integration tests

### Milestone 3: Content Verification and Publishing
- Implement content validation
- Develop Wikipedia-style formatting
- Create export capabilities
- Add end-to-end tests

### Milestone 4: User Interface and Deployment
- Develop web interface
- Implement search capabilities
- Add user feedback system
- Create deployment infrastructure

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

## License

This project is open source and available under the [MIT License](LICENSE).