feat: Add MCP server for generating notional data

- Implement data generation server with support for insurance data
- Add comprehensive test suite with 16 test cases
- Support custom schemas and data relationships
- Use faker, mimesis, numpy, and SDV for realistic data
- Pass all type checks with pyright and lint checks with ruff

Co-Authored-By: alexander@anthropic.com <alexander@anthropic.com>

src/datagen/README.md

@@ -0,0 +1,42 @@
+# MCP Data Generation Server
+
+This server implements the Model Context Protocol (MCP) to provide notional data generation capabilities using Python libraries including Faker, Mimesis, NumPy, and SDV.
+
+## Features
+
+- Generate synthetic data tables based on specified schemas and parameters
+- Support for multiple data generation libraries (Faker, Mimesis, SDV)
+- Configurable row counts and column specifications
+- Export data in CSV format
+
+## Installation
+
+```bash
+pip install mcp-server-datagen
+```
+
+## Usage
+
+The server exposes MCP tools for generating notional data:
+
+- `generate_tables`: Generate multiple related tables based on a schema
+- `define_schema`: Define table schemas with column specifications
+- `export_csv`: Export generated data to CSV files
+
+## Development
+
+1. Create virtual environment and install dependencies:
+```bash
+uv venv
+uv pip install -e ".[dev]"
+```
+
+2. Run type checking:
+```bash
+uv run --frozen pyright
+```
+
+3. Build package:
+```bash
+uv build
+```