Stock Pricing Data Generator

Generate synthetic stock pricing data for backtesting models.

Aim

This project generates realistic synthetic stock pricing data for testing and validating stock price forecasting models. The generated data mimics real-world stock price movements with appropriate price ranges and trading dates.

Related MCP server: mcp-sqlite3

Features

• Stocks: apple, microsoft, meta, google

• Exchanges: nyse, nasdaq

• Price Range: $100 - $1000

• Date Range: Configurable via CLI (default: last 90 days)

• Output: SQLite database (stocks.db)

Usage

uv run python generate_pricing.py

# Custom date range
uv run python generate_pricing.py --start 2026-01-01 --end 2026-04-25

Database Schema

CREATE TABLE stock_pricing (
    id INTEGER PRIMARY KEY,
    stock_name TEXT NOT NULL,
    stock_price REAL NOT NULL,
    date TEXT NOT NULL,
    stock_exchange TEXT NOT NULL
);

Requirements

• Python 3.x

• uv

Testing

uv run pytest test_generate_pricing.py -v

MCP Server

The MCP server is now running over STDIO for direct interaction with SQLite.

Start Server

uv run mcp_server.py

License

MIT