Number crunch
Statistical analysis suite: descriptive statistics, correlation analysis, and outlier detection on a single dataset.
3 tools run server-side in one request. You pay once, settle once, and get a single response - no orchestration, no per-step payments, and a partial-success envelope if any step fails. USDC over x402 on any supported chain.
When to use this pack
An agent has a series of numbers (prices, scores, measurements) and needs the full statistical picture in one call: central tendency, spread, whether any values are anomalous, and the trend direction.
Tools in this pack
All 3 run inside the single $0.050 call above. Each is also callable on its own if you only need one part.
- Stats summary POST /api/stats-summary Compute the full descriptive-stats panel for an array of numbers in one call: count, sum, mean, median, mode, stddev (sample), variance, min, max, range, q1, q3, IQR. Beats calling 12 separate tools when you already have the array in front of you.
- Correlation (Pearson) POST /api/correlation Pearson correlation coefficient between two equal-length numeric series. Returns r (the correlation, -1 to 1), r² (variance explained), n (sample size). Use this to ask things like: is a stock's daily return correlated with a macro indicator? Are two FRED series moving together?
- Outlier detection (IQR + z-score) POST /api/outliers Flag outliers in a numeric series using either the IQR rule (Tukey fences at 1.5·IQR - robust, default) or z-score (|z| > threshold - assumes normality). Returns the outlier values + their indices + the thresholds used so you can decide whether to trust them.
Workflow
- Compute descriptive statistics with stats-summary - count, mean, median, stddev, quartiles, min, max.
- Run correlation of the values against their indices (position trend) - r near +1/-1 means a clear upward/downward trend over the series.
- Detect outliers - IQR fence + z-score methods flag anomalous values the agent should investigate or exclude.
Call it directly
Any x402 client pays the 402 and gets the whole workflow back in one response:
npx agent402-client call number-crunch {"values":"10,12,15,11,50,13,14"}
Run it in Claude
claude mcp add agent402 -s user -- npx -y agent402-mcp@latest
Then paste this prompt into Claude:
Analyze the dataset [10,12,15,11,50,13,14] using Agent402: (1) stats-summary - descriptive stats. (2) correlation with x=values, y=indices - trend detection. (3) outliers - flag anomalies. Return {stats, trend, outliers}.