plot-mcp-worker

A serverless MCP chart rendering engine on Cloudflare Workers.
Let any AI agent generate PNG/SVG charts, STEM diagrams, and visualizations from a single JSON call.

Keywords: MCP server, Model Context Protocol, chart generation, function plot, data visualization, STEM diagram, physics force diagram, circuit schematic, 3D geometry, Venn diagram, Cloudflare Workers, serverless, SVG rendering, AI agent tools, Claude MCP, math plotter

Quick Start

Use with any MCP client

Add to your MCP client configuration (Claude Desktop, Cursor, etc.):

{
  "mcpServers": {
    "plot": {
      "url": "https://<your-worker>.<your-subdomain>.workers.dev/mcp"
    }
  }
}

No API key needed for the public endpoint. Your AI agent can now generate charts.

Fair use: The public endpoint is provided for experimentation and integration testing. For production use or higher-volume workloads, self-hosting is recommended.

Use via HTTP

curl -X POST https://<your-worker>.<your-subdomain>.workers.dev/mcp \
  -H "Content-Type: application/json" \
  -d '{
    "jsonrpc": "2.0", "id": 1,
    "method": "tools/call",
    "params": {
      "name": "plot_png_link",
      "arguments": {"expr": "sin(x)", "title": "Sine Wave"}
    }
  }'

Returns JSON with a png_url. Pre-rendered PNG, 5-minute cache.

Direct PNG/SVG URLs

https://<your-worker>.<your-subdomain>.workers.dev/png?d=<base64url-encoded-params>
https://<your-worker>.<your-subdomain>.workers.dev/plot?d=<base64url-encoded-params>

Use plot_png_link or plot tool to get properly encoded URLs.

Recommended Tools

Start here. These four tools cover 95% of use cases:

Tool	When to use
`plot` / `plot_png_link`	Single function or expression — `sin(x)`, `exp(-x)*cos(x)`, etc. Supports annotations, custom ranges, layout presets.
`plot_multi`	Multiple expressions overlaid — compare functions, show decompositions.
`plot_series`	Data-driven charts — line, scatter, bar (grouped/stacked), histogram, box plot, pie. Accepts raw data arrays with optional error bars and transforms.
`multi_plot`	Subplot grids — M×N layout of any chart types in one figure.

Legacy / Specialized Tools

These remain supported for compatibility and niche workflows. New integrations should prefer the four tools above.

Tool	Use case
`plot_bar`	Quick bar chart shorthand (categories + values)
`teaching`	Built-in math education templates (definite integral, derivative tangent, Fourier, projectile, etc.)
`analysis`	Statistical summaries — describe, correlation, groupby
`force_diagram_link`	Physics force diagrams
`circuit_diagram_link`	Circuit schematics
`venn_diagram_link`	Venn diagrams
`c_memory_diagram_link`	C memory layout diagrams
`plot_json`	Raw spec input (advanced)

Smart Defaults

The engine does a lot before you touch any option:

Axis Intelligence

Nice ticks: Step selection from 1, 2, 2.5, 5 × 10ⁿ — no ugly values like 0.72 or 1.2
Auto π-mode: Trig functions automatically get π-formatted x-axis (-2π, -π, 0, π, 2π)
Trig y-special: sin/cos gets [-1, -0.5, 0, 0.5, 1] instead of arbitrary decimals
0-symmetric: Math-style function plots default to symmetric y-axis around zero
Log scale: Set y_scale: "log" for logarithmic y-axis with proper tick formatting

Discontinuity Handling

Asymptote detection: Sign-flip + large Δy triggers path break — no vertical spikes at asymptotes
IQR bounds clamping: Extreme values near asymptotes (e.g., tan(x) at ±π/2) are automatically clamped using interquartile range filtering, keeping the y-axis readable

Visual Design

Dark theme by default: #0f172a card, #111827 plot area, #334155 grid — publication-ready out of the box
Legend outside plot area: Right-side reserved, never overlaps data
Canvas presets: Math (1000×720) for functions, Report (1200×720) for data charts
CJK support: 7500+ glyphs (GB2312 + punctuation + math symbols) via text-to-path pipeline
Color palette: #60a5fa, #f87171, #34d399, #fbbf24, #a78bfa, #22d3ee, #fb923c, #f472b6

Annotations

Three annotation types, placed in separate visual layers:

"annotations": [
  {"kind": "point", "x": 1.471, "y": 0.859, "label": "Peak", "color": "#fbbf24"},
  {"kind": "area", "x_min": 0.8, "x_max": 2.2, "label": "Region", "color": "#60a5fa", "opacity": 0.12},
  {"kind": "vertical_line", "x": 6.93, "label": "Half-life", "color": "#f87171"}
]

Layout: points → above-right of marker; areas → inside lower region; vertical lines → bottom of plot. Local collision avoidance is basic in the current version and will be improved.

Expression Syntax

Powered by expr-eval:

Functions: sin, cos, tan, exp, log, sqrt, abs, floor, ceil, round
Constants: pi, e
Operators: +, -, *, /, ^ (power), % (mod)

Response Shape

PNG link (plot, plot_multi, plot_series, multi_plot)

{
  "ok": true,
  "png_url": "https://<your-worker>.<your-subdomain>.workers.dev/png?d=...",
  "warnings": []
}

Debug mode (debug: true)

{
  "ok": true,
  "spec": { "xMin": -6.28, "xMax": 6.28, "yMin": -1.2, "yMax": 1.2 },
  "warnings": [{"type": "bounds", "message": "y-range clamped via IQR outlier removal"}],
  "debug": {
    "stages": [
      {"name": "raw", "input": 400, "output": 400},
      {"name": "downsample", "method": "minmax", "input": 400, "output": 200}
    ]
  }
}

Error

{
  "ok": false,
  "error": {
    "type": "transform",
    "message": "normalize skipped due to error bars"
  }
}

Observability & Safety

The engine doesn't just draw — it explains what it did and warns when something might be wrong.

Debug Mode

{"tool": "plot_series", "arguments": {
  "debug": true,
  "series": [{"type": "line", "name": "data", "points": [[1,2],[2,5],[3,3]]}]
}}

Returns a debug object with pipeline stages:

{
  "debug": {
    "stages": [
      {"name": "raw", "input": 3, "output": 3},
      {"name": "downsample", "method": "minmax", "input": 3, "output": 3}
    ]
  }
}

Structured Warnings

The engine emits warnings when it makes automatic decisions:

{
  "warnings": [
    {"type": "transform", "message": "normalize skipped due to error bars"},
    {"type": "bounds", "message": "y-range clamped via IQR outlier removal (42 of 400 points excluded)"}
  ]
}

Transform Policy

Control how aggressively the engine applies automatic transforms:

"transformPolicy": "strict"       // fail on unsupported transforms
"transformPolicy": "best-effort"  // skip silently (default)

Showcase

1. Trigonometric Composition

sin, cos, and their sum — auto-detected π-mode x-axis, trig y-special ticks.

{"tool": "plot_multi", "arguments": {
  "exprs": ["sin(x)", "cos(x)", "sin(x)+cos(x)"],
  "labels": ["sin(x)", "cos(x)", "sin(x) + cos(x)"],
  "x_min": -6.283, "x_max": 6.283,
  "title": "Trigonometric Composition"
}}

2. Square Wave — Fourier Series Approximation

Progressively adding odd harmonics. 4 series, auto π-axis.

{"tool": "plot_multi", "arguments": {
  "exprs": ["sin(x)", "sin(x)+sin(3*x)/3", "sin(x)+sin(3*x)/3+sin(5*x)/5", "sin(x)+sin(3*x)/3+sin(5*x)/5+sin(7*x)/7"],
  "labels": ["1 term", "2 terms", "3 terms", "4 terms"],
  "x_min": -6.283, "x_max": 6.283,
  "title": "Square Wave — Fourier Series Approximation"
}}

3. tan(x) — Asymptote-Aware Rendering

Automatic discontinuity detection with IQR bounds clamping. No spikes, no vertical lines connecting ±∞. Y-range stays readable near asymptotes.

{"tool": "plot_png_link", "arguments": {
  "expr": "tan(x)",
  "x_min": -4.712, "x_max": 4.712,
  "title": "tan(x) — Discontinuity Detection"
}}

4. sinc(x) = sin(x)/x

Removable singularity handling at x=0.

{"tool": "plot_png_link", "arguments": {
  "expr": "sin(x)/x",
  "x_min": -15, "x_max": 15,
  "title": "sinc(x) = sin(x)/x"
}}

5. 1/(x²-1) — Rational Function with Asymptote Annotations

Vertical asymptote markers at x = ±1. Pole gaps rendered without artifact spikes.

{"tool": "plot_png_link", "arguments": {
  "expr": "1/(x^2-1)",
  "x_min": -4, "x_max": 4,
  "title": "1/(x²-1) — Rational Function",
  "annotations": [
    {"kind": "vertical_line", "x": -1, "label": "x = -1", "color": "#f87171"},
    {"kind": "vertical_line", "x":  1, "label": "x = 1",  "color": "#f87171"}
  ]
}}

6. Damped Oscillation

Exponential decay × trig — automatic nice ticks, smooth rendering across 15 units.

{"tool": "plot_png_link", "arguments": {
  "expr": "exp(-0.3*x)*sin(2*x)",
  "x_min": 0, "x_max": 15,
  "title": "Damped Oscillation: e^(-0.3x)·sin(2x)"
}}

7. |sin(x)|·cos(x) — Rectified Product

Absolute value composition — non-trivial waveform with sign changes.

{"tool": "plot_png_link", "arguments": {
  "expr": "abs(sin(x))*cos(x)",
  "x_min": -10, "x_max": 10,
  "title": "|sin(x)|·cos(x) — Rectified Product"
}}

8. Gaussian Mixture Model

Three Gaussians with different means and variances.

{"tool": "plot_multi", "arguments": {
  "exprs": ["exp(-x*x/2)/sqrt(2*3.14159)", "0.6*exp(-(x-2)*(x-2)/1.5)/sqrt(2*3.14159*1.5)", "0.4*exp(-(x+1.5)*(x+1.5)/0.8)/sqrt(2*3.14159*0.8)"],
  "labels": ["N(0,1)", "0.6·N(2,1.5)", "0.4·N(-1.5,0.8)"],
  "x_min": -6, "x_max": 8,
  "title": "Gaussian Mixture Model"
}}

9. Decaying Sine with Annotations

Area shading, point markers, vertical line — all annotation types in one chart. Points placed at mathematically correct peak locations (derived from f'(x)=0). Annotation layout uses layered placement: points above-right, areas inside-lower, vertical lines at bottom.

{"tool": "plot_png_link", "arguments": {
  "expr": "sin(x)*exp(-0.1*x)",
  "x_min": 0, "x_max": 20,
  "title": "Decaying Sine with Annotations",
  "annotations": [
    {"kind": "area", "x_min": 0.8, "x_max": 2.2, "label": "1st peak zone", "color": "#60a5fa", "opacity": 0.12},
    {"kind": "area", "x_min": 7.0, "x_max": 8.5, "label": "2nd peak zone", "color": "#34d399", "opacity": 0.12},
    {"kind": "point", "x": 1.471, "y": 0.859, "label": "Peak 1", "color": "#fbbf24"},
    {"kind": "point", "x": 7.754, "y": 0.458, "label": "Peak 2", "color": "#fbbf24"},
    {"kind": "vertical_line", "x": 6.93, "label": "Half-life ≈ 6.93", "color": "#f87171"}
  ]
}}

10. Multi-Series Business Chart with Error Bars

Forecast vs Actual vs Target — symmetric error bars on scatter.

{"tool": "plot_series", "arguments": {
  "title": "Q1-Q4 Revenue Forecast vs Actual",
  "xlabel": "Quarter", "ylabel": "Revenue (M USD)",
  "series": [
    {"name": "Forecast", "type": "line+scatter", "points": [[1,120],[2,185],[3,310],[4,490]], "color": "#60a5fa", "error": [8,12,20,35]},
    {"name": "Actual",   "type": "line+scatter", "points": [[1,135],[2,178],[3,345],[4,510]], "color": "#f87171", "error": [5,10,15,25]},
    {"name": "Target",   "type": "line",         "points": [[1,150],[2,200],[3,300],[4,450]], "color": "#34d399"}
  ]
}}

11. Grouped Bar Chart with Error Bars

3 models × 4 tests — per-bar error bars, auto-category labels.

{"tool": "plot_series", "arguments": {
  "title": "Performance Benchmarks",
  "xlabel": "Test", "ylabel": "Score",
  "bar_style": "grouped",
  "series": [
    {"name": "Model A", "type": "bar", "points": [[0,92],[1,78],[2,85],[3,95]], "group": "g", "color": "#60a5fa", "error": [2,3,2,1]},
    {"name": "Model B", "type": "bar", "points": [[0,88],[1,82],[2,91],[3,87]], "group": "g", "color": "#f87171", "error": [3,2,1,2]},
    {"name": "Model C", "type": "bar", "points": [[0,95],[1,74],[2,79],[3,90]], "group": "g", "color": "#34d399", "error": [1,4,3,2]}
  ]
}}

12. Stacked Bar Chart

Cloud cost breakdown — compute, storage, network stacked by month.

{"tool": "plot_series", "arguments": {
  "title": "Cloud Infrastructure Costs — Stacked",
  "xlabel": "Month", "ylabel": "Cost ($)",
  "bar_style": "stacked",
  "series": [
    {"name": "Compute", "type": "bar", "points": [[1,3200],[2,3500],[3,4100],[4,4800],[5,5200],[6,5600]], "group": "g", "color": "#60a5fa"},
    {"name": "Storage", "type": "bar", "points": [[1,1200],[2,1400],[3,1600],[4,1900],[5,2200],[6,2500]], "group": "g", "color": "#34d399"},
    {"name": "Network", "type": "bar", "points": [[1,800],[2,900],[3,1100],[4,1300],[5,1500],[6,1800]], "group": "g", "color": "#fbbf24"}
  ]
}}

13. Pie Chart

Team time allocation with percentage labels.

{"tool": "plot_series", "arguments": {
  "title": "Time Allocation — AI Research Team",
  "series": [{"type": "pie", "name": "team", "labels": ["Training","Data Prep","Evaluation","Infra","Meetings","Research"], "values": [35,20,15,12,8,10]}]
}}

14. Histogram

Response latency distribution with auto-binning.

{"tool": "plot_series", "arguments": {
  "title": "Response Latency Distribution",
  "xlabel": "Latency", "ylabel": "Count",
  "series": [{"type": "hist", "name": "latency", "data": [12,15,18,22,25,28,30,32,35,38,41,45,48,52,55,58,62,65,68,72,75,78,82,85,88,92,95,98,102,105,108,112,115,118,122,125,128,132,135,138,142,145,148,152,155,158,162], "bins": 10}]
}}

15. Box Plot

Model accuracy comparison — median, quartiles, whiskers, outliers.

{"tool": "plot_series", "arguments": {
  "title": "Model Accuracy Across Datasets",
  "ylabel": "Accuracy (%)",
  "series": [
    {"type": "box", "name": "GPT-4",  "data": [82,85,87,89,90,91,92,93,94,95,97]},
    {"type": "box", "name": "Claude", "data": [80,84,86,88,90,91,92,93,95,96,98]},
    {"type": "box", "name": "Gemini", "data": [75,79,83,85,87,89,90,92,93,94,96]}
  ]
}}

16. Log Scale

Training loss over 10 epochs — y-axis automatically switches to logarithmic tick formatting.

{"tool": "plot_series", "arguments": {
  "title": "Training Loss (Log Scale)",
  "xlabel": "Epoch", "ylabel": "Loss",
  "y_scale": "log",
  "series": [{"name": "Loss", "type": "line", "points": [[1,2.5],[2,1.8],[3,0.95],[4,0.42],[5,0.18],[6,0.072],[7,0.031],[8,0.014],[9,0.006],[10,0.003]], "color": "#a78bfa"}]
}}

17. Scatter with Asymmetric Error Bars

Asymmetric uncertainty — error: { plus: [...], minus: [...] }.

{"tool": "plot_series", "arguments": {
  "title": "Experimental Measurements — Asymmetric Uncertainty",
  "xlabel": "Temperature (K)", "ylabel": "Conductivity (S/m)",
  "series": [{"name": "Measurement", "type": "scatter", "points": [[200,0.12],[250,0.28],[300,0.45],[350,0.67],[400,0.88],[450,1.05],[500,1.22]], "color": "#f472b6", "error": {"plus": [0.02,0.03,0.05,0.08,0.06,0.04,0.03], "minus": [0.01,0.02,0.03,0.05,0.04,0.03,0.02]}}]
}}

18. Transform Pipeline — Raw → Smoothed → Normalized

Three views of the same noisy data: raw scatter, smoothed line (window=3), and min-max normalized.

{"tool": "plot_series", "arguments": {
  "title": "Raw → Smoothed → Normalized Pipeline",
  "xlabel": "Sample", "ylabel": "Value",
  "series": [
    {"name": "Raw",        "type": "scatter", "points": [[0,2.1],[1,8.3],[2,4.5],[3,12.1],[4,6.2],[5,15.8],[6,9.1],[7,3.2],[8,11.5],[9,7.8],[10,14.2],[11,5.5]], "color": "#475569"},
    {"name": "Smoothed",   "type": "line",    "points": [[0,2.1],[1,8.3],[2,4.5],[3,12.1],[4,6.2],[5,15.8],[6,9.1],[7,3.2],[8,11.5],[9,7.8],[10,14.2],[11,5.5]], "color": "#60a5fa", "transforms": [{"type": "smooth", "window": 3}]},
    {"name": "Normalized", "type": "line",    "points": [[0,2.1],[1,8.3],[2,4.5],[3,12.1],[4,6.2],[5,15.8],[6,9.1],[7,3.2],[8,11.5],[9,7.8],[10,14.2],[11,5.5]], "color": "#f472b6", "transforms": [{"type": "normalize", "method": "minmax"}]}
  ]
}}

19. 2×2 Subplot Grid

Four different chart types in one figure — line, scatter, function.

{"tool": "multi_plot", "arguments": {
  "title": "Function Gallery",
  "rows": 2, "cols": 2,
  "plots": [
    {"row": 0, "col": 0, "title": "sin(x)",    "series": [{"type": "line",    "name": "sin(x)",   "points": [[-3.14,0],[-1.57,-1],[0,0],[1.57,1],[3.14,0]],  "color": "#60a5fa"}]},
    {"row": 0, "col": 1, "title": "x²",         "series": [{"type": "line",    "name": "x²",       "points": [[-3,9],[-2,4],[-1,1],[0,0],[1,1],[2,4],[3,9]],   "color": "#f87171"}]},
    {"row": 1, "col": 0, "title": "exp(-x)",    "series": [{"type": "line",    "name": "exp(-x)",  "points": [[-2,7.39],[-1,2.72],[0,1],[1,0.37],[2,0.14]],    "color": "#34d399"}]},
    {"row": 1, "col": 1, "title": "log(x)",     "series": [{"type": "scatter", "name": "log(x)",   "points": [[0.1,-2.3],[0.5,-0.69],[1,0],[2,0.69],[5,1.6]], "color": "#fbbf24"}]}
  ]
}}

20. Teaching Template — Definite Integral

Built-in teaching module: shaded integral region, formula, bounds.

{"tool": "teaching", "arguments": {
  "topic": "definite_integral",
  "params": {"expr": "x^2 - x + 1", "a": 0, "b": 3},
  "title": "∫₀³ (x² - x + 1) dx"
}}

Data Transforms

Pipeline transforms on data series:

"transforms": [
  {"type": "smooth", "window": 5},
  {"type": "normalize", "method": "minmax"},
  {"type": "normalize", "method": "zscore"},
  {"type": "rolling_avg", "window": 3}
]

Downsampling is automatic for large datasets (minmax algorithm preserves visual extrema).

Error Bars

Three formats:

"error": [2, 3, 2, 1]                          // symmetric per-point
"error": 5                                      // constant for all points
"error": {"plus": [0.02,0.03], "minus": [0.01,0.02]}  // asymmetric

Current Strengths & Limits

What works well

Dark-theme defaults that look good without configuration
π-aware trig axes with automatic detection
Minmax downsampling that preserves visual extrema
Structured warnings and debug traces for observability
CJK text via path-based rendering (no client font dependency)
Asymptote-aware function plotting with IQR bounds clamping
Annotation system with three semantic types and layered placement

Current limits

Annotation local collision avoidance is basic — labels in the same region may overlap. Full layout engine planned for next release.
Symbolic tick marks beyond π (e.g., √2, e) are not yet auto-detected.
Function plot layout prioritizes readability over full symbolic analysis.
Some legacy tools (plot_bar, plot_json) remain for backward compatibility.

Self-Host (Deploy Your Own)

Prerequisites

Node.js 20+
Wrangler CLI (npm install -g wrangler)
A Cloudflare account (free tier works)
Cloudflare Workers KV namespace (for font storage and short-link URLs)

Steps

# 1. Clone
git clone https://github.com/lingion/plot-mcp-worker.git
cd plot-mcp-worker

# 2. Install dependencies
npm install

# 3. Create KV namespace
npx wrangler kv namespace create SHORT_LINKS
# Note the `id` from the output

# 4. Update wrangler.toml with your KV namespace ID

# 5. Upload fonts to KV (for CJK support)
#
# CJK text is rendered via text-to-path (opentype.js), embedding font outlines
# directly into SVG. You need a subset font stored in KV:
#   - Use pyftsubset to extract GB2312 + punctuation + math symbols
#   - Add --no-hinting to keep file under 3 MB (wrangler kv put silent-fails above that)
npx wrangler kv key put "font:arial-unicode-cn-gb2312" \
  --namespace-id YOUR_KV_ID --path subset.ttf --remote

# Latin text uses embedded font buffers in the Worker. If you want to override
# the default Latin glyphs, upload a TTF with full ASCII coverage:
npx wrangler kv key put "font:arial-sans" \
  --namespace-id YOUR_KV_ID --path latin-font.ttf --remote

# Note: You are responsible for font licensing when self-hosting.

# 6. Deploy
npx wrangler deploy

Custom Domain (Optional)

Add a route in wrangler.toml:

[[routes]]
pattern = "plot.yourdomain.com/*"
zone_name = "yourdomain.com"

Architecture

Client (AI agent)
    │
    ▼
┌─────────────────────────────┐
│   Cloudflare Worker         │
│                             │
│  MCP endpoint (/mcp)        │◄── JSON-RPC tool calls
│         │                   │
│         ▼                   │
│  Spec normalization         │    Input → PlotSpec
│         │                   │
│         ▼                   │
│  SVG generation             │    Pure string templates
│         │                   │
│         ▼                   │
│  CJK text-to-path           │    opentype.js (font from KV)
│         │                   │
│         ▼                   │
│  PNG rasterization          │    resvg-wasm
│         │                   │
│         ▼                   │
│  KV short-link storage      │    5-min TTL
│                             │
└─────────────────────────────┘
    │
    ▼
  PNG URL → client

No headless browser. No external storage. Everything runs in a single Cloudflare Worker with KV.

Bundle & Asset Sizes

Worker bundle: roughly ~1 MB gzipped (well within CF free tier 3 MB limit)
CJK font subset size depends on chosen font assets; stored in KV and cached in Worker memory

MCP Tools Reference

Tool	Description	Key Parameters
`plot` / `plot_png_link`	Single expression chart	`expr`, `title`, `x_min`, `x_max`, `annotations`
`plot_multi`	Multiple expressions overlaid	`exprs[]`, `labels[]`, `title`
`plot_series`	Data-driven charts	`series[]` with `type`, `points`, `color`, `error`, `transforms`
`multi_plot`	Subplot grid	`rows`, `cols`, `plots[]`

Legacy / Specialized

Tool	Description
`plot_bar`	Quick bar chart (categories + values)
`teaching`	Math education templates: `definite_integral`, `derivative_tangent`, `fourier_series`, `projectile`, `simple_harmonic`, `energy_conservation`, `rc_circuit`, `parabola`
`analysis`	Statistical analysis: `describe`, `corr`, `groupby`
`force_diagram_link`	Physics force diagrams
`circuit_diagram_link`	Circuit schematics
`venn_diagram_link`	Venn diagrams
`c_memory_diagram_link`	C memory layout
`plot_json`	Raw spec input (advanced)

Documentation

Operation Guide — step-by-step user manual covering all 40+ tools, endpoints, local development, and troubleshooting
Technical Write-up — architecture deep-dive: expression parser, 5-transform data pipeline, smart axis intelligence, CJK text-to-path, diagram generators

License

CC BY-NC-SA 4.0

Name		Name	Last commit message	Last commit date
Latest commit History 115 Commits
docs		docs
scripts		scripts
src		src
.gitignore		.gitignore
LICENSE		LICENSE
README.md		README.md
README.zh-CN.md		README.zh-CN.md
README_CN.md		README_CN.md
RELEASE_NOTES.md		RELEASE_NOTES.md
capabilities.json		capabilities.json
package-lock.json		package-lock.json
package.json		package.json
tsconfig.json		tsconfig.json
wrangler.toml		wrangler.toml

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plot-mcp-worker

Quick Start

Use with any MCP client

Use via HTTP

Direct PNG/SVG URLs

Recommended Tools

Legacy / Specialized Tools

Smart Defaults

Axis Intelligence

Discontinuity Handling

Visual Design

Annotations

Expression Syntax

Response Shape

PNG link (plot, plot_multi, plot_series, multi_plot)

Debug mode (debug: true)

Error

Observability & Safety

Debug Mode

Structured Warnings

Transform Policy

Showcase

1. Trigonometric Composition

2. Square Wave — Fourier Series Approximation

3. tan(x) — Asymptote-Aware Rendering

4. sinc(x) = sin(x)/x

5. 1/(x²-1) — Rational Function with Asymptote Annotations

6. Damped Oscillation

7. |sin(x)|·cos(x) — Rectified Product

8. Gaussian Mixture Model

9. Decaying Sine with Annotations

10. Multi-Series Business Chart with Error Bars

11. Grouped Bar Chart with Error Bars

12. Stacked Bar Chart

13. Pie Chart

14. Histogram

15. Box Plot

16. Log Scale

17. Scatter with Asymmetric Error Bars

18. Transform Pipeline — Raw → Smoothed → Normalized

19. 2×2 Subplot Grid

20. Teaching Template — Definite Integral

Data Transforms

Error Bars

Current Strengths & Limits

What works well

Current limits

Self-Host (Deploy Your Own)

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Steps

Custom Domain (Optional)

Architecture

Bundle & Asset Sizes

MCP Tools Reference

Recommended

Legacy / Specialized

Documentation

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