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Math & Statistics Graphing Engine

by @architectds

Math & statistics graphing, computation, visualization and validation engine

Versionv1.0.0
Downloads1,059
TERMINAL
clawhub install mathgraphs

πŸ“– About This Skill


name: mathgraphs version: 1.0.0 description: "Math & statistics graphing, computation, visualization and validation engine" author: MathTalking homepage: https://mathtalking.com mcp_servers: - url: https://mathtalking.com/api/mcp transport: streamable-http tags: - math - graphing - statistics - visualization - education - plot - geometry

Math & Statistics Graphing Engine

You have access to an interactive math and statistics graphing engine via MCP. It computes and renders results β€” roots, extrema, intersections, regression, hypothesis tests β€” on interactive graphs.

When to use this skill

  • User asks to graph, plot, or visualize any math
  • User needs to verify a mathematical result visually
  • You computed an answer and want to show it, not just describe it
  • Data needs statistical visualization (histogram, regression, distribution fit)
  • Geometry needs precise rendering (triangles, circles, constructions)
  • Tools

    plot_graph β€” Math Visualization

    Plot functions, points, segments, labels, and shapes. Auto-computes roots, extrema, and intersections.

    Element types:

  • function: expression like "x^2-4", "sin(x)", "x^2+y^2=1", "(cos(t),sin(t))"
  • points: array of {x, y} coordinates with optional label
  • segment: line from (x1,y1) to (x2,y2) with optional arrow/dashed
  • label: text at position (x, y)
  • triangle: three vertices (x1,y1,x2,y2,x3,y3)
  • box: edge + height for bar charts
  • compute_stats β€” Descriptive Statistics

    Input: array of numbers. Returns mean, median, std, min, max, quartiles.

    add_histogram β€” Histogram

    Input: array of numbers. Auto-bins and draws bars.

    add_regression β€” Regression

    Input: array of {x,y} points. Fits linear/quadratic/exponential/power. Returns RΒ².

    fit_distribution β€” Distribution Fitting

    Input: array of numbers. Fits normal/uniform/exponential. Returns best fit.

    test_hypothesis β€” Hypothesis Test

    Input: data groups + test type. Returns p-value with visual rejection region.

    Important

  • All tools return an interactive URL β€” always share it with the user
  • The graph is live: user can zoom, pan, add functions, adjust sliders
  • Results are computed from the graph, not generated β€” no hallucinated curves
  • Supports 9 languages: en, zh, zh-TW, ja, ko, es, fr, de, pt-BR