MCP Autonomous Analyst

# tools/synthetic_data.py import numpy as np import pandas as pd def generate_synthetic_data(rows: int = 3000) -> pd.DataFrame: np.random.seed() df = pd.DataFrame({ "feature_1": np.random.normal(50, 10, rows), "feature_2": np.random.normal(30, 5, rows), "category": np.random.choice(["A", "B", "C"], rows) }) outliers = pd.DataFrame({ "feature_1": np.random.normal(150, 5, 20), "feature_2": np.random.normal(90, 5, 20), "category": ["Outlier"] * 20 }) return pd.concat([df, outliers], ignore_index=True)