A React data visualization library designed for AI-assisted development.

Simple charts in 5 lines. Network graphs, streaming data, and coordinated dashboards when you need them. Structured schemas and an MCP server so AI coding assistants generate correct chart code on the first try.

import { LineChart } from "semiotic"

<LineChart
  data={salesData}
  xAccessor="month"
  yAccessor="revenue"
/>

Why Semiotic

Semiotic is a data visualization library for React that combines broad chart coverage with first-class AI tooling. It handles the chart types that most libraries skip — network graphs, streaming data, statistical distributions, coordinated views — and ships with machine-readable schemas so LLMs can generate correct code without examples.

Built for AI-assisted development

Semiotic ships with everything an AI coding assistant needs to generate correct visualizations without trial and error:

• semiotic/ai — a single import with all 37 chart components, optimized for LLM code generation
• ai/schema.json — machine-readable prop schemas for every component
• npx semiotic-mcp — an MCP server for tool-based chart rendering in any MCP client
• npx semiotic-ai --doctor — validate component + props JSON from the command line with typo suggestions and anti-pattern detection
• diagnoseConfig(component, props) — programmatic anti-pattern detector with 12 checks and actionable fixes
• CLAUDE.md — instruction files auto-synced for Claude, Cursor, Copilot, Windsurf, and Cline
• llms.txt — machine-readable documentation following the emerging standard

Every chart includes a built-in error boundary, dev-mode validation warnings with typo suggestions, and accessibility features (canvas aria-label, keyboard-navigable legends, aria-live tooltips, SVG <title>/<desc>) so AI-generated code fails gracefully with actionable diagnostics instead of a blank screen.

Beyond standard charts

Network visualization. Force-directed graphs, Sankey diagrams, chord diagrams, tree layouts, treemaps, circle packing, and orbit diagrams — all as React components with the same prop API as LineChart.

Streaming data. Realtime charts render on canvas at 60fps with a ref-based push API. Built-in decay, pulse, and staleness encoding for monitoring dashboards.

Coordinated views. LinkedCharts provides hover cross-highlighting, brush cross-filtering, and selection synchronization across any combination of chart types — zero wiring.

Geographic visualization. Choropleth maps, proportional symbol maps, flow maps with animated particles, and distance cartograms — all canvas-rendered with d3-geo projections, zoom/pan, tile basemaps, and drag-rotate globe spinning.

Statistical summaries. Box plots, violin plots, swarm plots, histograms, LOESS smoothing, forecast with confidence envelopes, and anomaly detection. Marginal distribution graphics on scatterplot axes with a single prop.

Start simple, go deep

Layer	For	Example
Charts	Common visualizations with sensible defaults	<LineChart data={d} xAccessor="x" yAccessor="y" />
Frames	Full control over rendering, interaction, and layout	<StreamXYFrame chartType="line" lineStyle={...} />

Every Chart component accepts a frameProps prop to access the underlying Frame API without leaving the simpler interface.

Serialization and interop

Charts serialize to JSON and back: toConfig, fromConfig, toURL, copyConfig, configToJSX. Have Vega-Lite specs? fromVegaLite(spec) translates them to Semiotic configs — works with configToJSX() for full round-trip from notebooks and AI-generated specs.

When to use something else

Need a standard bar or line chart for a dashboard you'll never need to customize beyond colors and labels? Recharts has a larger ecosystem and more community examples. Need GPU-accelerated rendering for millions of data points? Apache ECharts handles that scale.

Semiotic is for projects that outgrow those libraries — when you need network graphs alongside time series, streaming data alongside static snapshots, or coordinated views across chart types.

Install

npm install semiotic

Requires React 18.1+ or React 19.

Quick Examples

Coordinated Dashboard

Hover one chart, highlight the same data in another — zero wiring:

import { LinkedCharts, Scatterplot, BarChart } from "semiotic"

<LinkedCharts>
  <Scatterplot
    data={data} xAccessor="age" yAccessor="income" colorBy="region"
    linkedHover={{ name: "hl", fields: ["region"] }}
    selection={{ name: "hl" }}
  />
  <BarChart
    data={summary} categoryAccessor="region" valueAccessor="total"
    selection={{ name: "hl" }}
  />
</LinkedCharts>

Streaming Metrics with Decay

Live data fades old points, flashes new ones, flags stale feeds:

import { RealtimeLineChart } from "semiotic"

const chartRef = useRef()
chartRef.current.push({ time: Date.now(), value: cpuLoad })

<RealtimeLineChart
  ref={chartRef}
  timeAccessor="time"
  valueAccessor="value"
  decay={{ type: "exponential", halfLife: 100 }}
  staleness={{ threshold: 5000, showBadge: true }}
/>

Network Graphs

Force-directed graphs and Sankey diagrams — same API as LineChart:

import { ForceDirectedGraph, SankeyDiagram } from "semiotic"

<ForceDirectedGraph
  nodes={people} edges={friendships}
  colorBy="team" nodeSize={8} showLabels
/>

<SankeyDiagram
  edges={budgetFlows}
  sourceAccessor="from" targetAccessor="to" valueAccessor="amount"
/>

Geographic Visualization

Choropleth maps, flow maps, and distance cartograms with canvas rendering, zoom/pan, tile basemaps, and animated particles:

import { ChoroplethMap, FlowMap, DistanceCartogram } from "semiotic/geo"

<ChoroplethMap
  areas={geoJsonFeatures} valueAccessor="gdp"
  colorScheme="viridis" projection="equalEarth" zoomable tooltip
/>

<FlowMap
  nodes={airports} flows={routes} valueAccessor="passengers"
  showParticles particleStyle={{ color: "source", speedMultiplier: 1.5 }}
/>

<DistanceCartogram
  points={cities} center="rome" costAccessor="travelDays"
  showRings costLabel="days" lines={routes}
/>

Streaming System Monitor

Live service topology with threshold alerting and click-to-inspect:

import { StreamNetworkFrame, ChartContainer, DetailsPanel, LinkedCharts } from "semiotic"

const chartRef = useRef()
chartRef.current.push({ source: "API", target: "Orders", value: 15 })

<LinkedCharts>
  <ChartContainer title="System Monitor" status="live"
    detailsPanel={
      <DetailsPanel position="right" trigger="click">
        {(datum) => <div>{datum.id}: {datum.value} req/s</div>}
      </DetailsPanel>
    }>
    <StreamNetworkFrame ref={chartRef} chartType="sankey"
      showParticles particleStyle={{ proportionalSpeed: true }}
      thresholds={{ metric: n => n.value, warning: 100, critical: 250 }}
    />
  </ChartContainer>
</LinkedCharts>

Standard Charts

Line, bar, scatter, area — all the basics, with sensible defaults:

import { LineChart, BarChart } from "semiotic"

<LineChart
  data={salesData}
  xAccessor="month" yAccessor="revenue"
  curve="monotoneX" showPoints
/>

<BarChart
  data={categoryData}
  categoryAccessor="department" valueAccessor="sales"
  orientation="horizontal" colorBy="region"
/>

All Chart Components

Category	Components
XY	LineChart AreaChart StackedAreaChart Scatterplot ConnectedScatterplot BubbleChart Heatmap QuadrantChart MinimapChart
Categorical	BarChart StackedBarChart GroupedBarChart SwarmPlot BoxPlot Histogram ViolinPlot RidgelinePlot DotPlot PieChart DonutChart
Network	ForceDirectedGraph ChordDiagram SankeyDiagram TreeDiagram Treemap CirclePack OrbitDiagram
Geo	ChoroplethMap ProportionalSymbolMap FlowMap DistanceCartogram
Realtime	RealtimeLineChart RealtimeHistogram RealtimeSwarmChart RealtimeWaterfallChart RealtimeHeatmap
Coordination	LinkedCharts ScatterplotMatrix
Layout	ChartGrid ContextLayout CategoryColorProvider
Frames	StreamXYFrame StreamOrdinalFrame StreamNetworkFrame StreamGeoFrame

Vega-Lite Translation

Paste a Vega-Lite spec, get a Semiotic chart:

import { fromVegaLite } from "semiotic/data"
import { configToJSX, fromConfig } from "semiotic"

const config = fromVegaLite({
  mark: "bar",
  data: { values: [{ a: "A", b: 28 }, { a: "B", b: 55 }] },
  encoding: {
    x: { field: "a", type: "nominal" },
    y: { field: "b", type: "quantitative" },
  },
})

// Render directly
const { componentName, props } = fromConfig(config)
// → componentName: "BarChart", props: { data, categoryAccessor: "a", valueAccessor: "b" }

// Or generate JSX code
configToJSX(config)
// → <BarChart data={[...]} categoryAccessor="a" valueAccessor="b" />

Supports bar, line, area, point, rect, arc, tick marks with encoding translation for color, size, aggregation, and binning.

Smaller Bundles

Import only what you need:

import { LineChart } from "semiotic/xy"                 // ~156 KB
import { BarChart } from "semiotic/ordinal"              // ~124 KB
import { ForceDirectedGraph } from "semiotic/network"    // ~123 KB
import { ChoroplethMap } from "semiotic/geo"             // ~102 KB (+ d3-geo peer)
import { LineChart } from "semiotic/ai"                  // ~397 KB (all HOCs)

Granular entry points export only v3 Stream Frames and HOC charts — no legacy utilities or backwards-compatibility shims.

TypeScript

Built with strict: true. Full type definitions ship with the package. Generics for type-safe accessors:

interface Sale { month: number; revenue: number }

<LineChart<Sale>
  data={sales}
  xAccessor="month"    // TS validates this is keyof Sale
  yAccessor="revenue"
/>

Server-Side Rendering

All chart components render SVG automatically in server environments — no special imports or configuration needed:

// Works in Next.js App Router, Remix, Astro — same component, same props
import { LineChart } from "semiotic"

// Server: renders <svg> with path/circle/rect elements
// Client: renders <canvas> with SVG overlay for axes
<LineChart data={data} xAccessor="date" yAccessor="value" />

For standalone SVG generation (email, OG images, PDF), use the server entry point:

import { renderToStaticSVG } from "semiotic/server"

const svg = renderToStaticSVG("xy", {
  lines: [{ coordinates: data }],
  xAccessor: "date",
  yAccessor: "value",
  size: [600, 400],
})

MCP Server

Semiotic ships with an MCP server that lets AI coding assistants render charts, diagnose configuration problems, discover schemas, and get chart recommendations via tool calls.

Setup

Add to your MCP client config (e.g. claude_desktop_config.json for Claude Desktop):

{
  "mcpServers": {
    "semiotic": {
      "command": "npx",
      "args": ["semiotic-mcp"]
    }
  }
}

No API keys or authentication required. The server runs locally via stdio.

Tools

Tool	Description
renderChart	Render a Semiotic chart to static SVG. Supports the components returned by getSchema that are marked [renderable]. Pass { component: "LineChart", props: { data: [...], xAccessor: "x", yAccessor: "y" } }. Returns SVG string or validation errors with fix suggestions.
getSchema	Return the prop schema for a specific component. Pass { component: "LineChart" } to get its props, or omit component to list all 30 chart types. Use before renderChart to look up valid props.
suggestChart	Recommend chart types for a data sample. Pass { data: [{...}, ...] } with 1–5 sample objects. Optionally include intent ("comparison", "trend", "distribution", "relationship", "composition", "geographic", "network", "hierarchy"). Returns ranked suggestions with example props.
diagnoseConfig	Check a chart configuration for common problems — empty data, bad dimensions, missing accessors, wrong data shape, and more. Returns a human-readable diagnostic report with actionable fixes.
reportIssue	Generate a pre-filled GitHub issue URL for bug reports or feature requests. Pass { title: "...", body: "...", labels: ["bug"] }. Returns a URL the user can open to submit.

Example: get schema for a component

Tool: getSchema
Args: { "component": "LineChart" }
→ Returns: { "name": "LineChart", "description": "...", "parameters": { "properties": { "data": ..., "xAccessor": ..., ... } } }

Example: suggest a chart for your data

Tool: suggestChart
Args: {
  "data": [
    { "month": "Jan", "revenue": 120, "region": "East" },
    { "month": "Feb", "revenue": 180, "region": "West" }
  ]
}
→ Returns:
  1. BarChart (high confidence) — categorical field (region) with values (revenue)
  2. StackedBarChart (medium confidence) — two categorical fields (month, region)
  3. DonutChart (medium confidence) — 2 categories — proportional composition

Example: render a chart

Tool: renderChart
Args: {
  "component": "BarChart",
  "props": {
    "data": [
      { "category": "Q1", "revenue": 120 },
      { "category": "Q2", "revenue": 180 },
      { "category": "Q3", "revenue": 150 }
    ],
    "categoryAccessor": "category",
    "valueAccessor": "revenue"
  }
}
→ Returns: <svg>...</svg>

Example: diagnose a broken config

Tool: diagnoseConfig
Args: { "component": "LineChart", "props": { "data": [] } }
→ Returns: ✗ [EMPTY_DATA] data is an empty array — Fix: provide at least one data point

Example: report an issue

Tool: reportIssue
Args: {
  "title": "Bug: BarChart tooltip shows undefined for custom accessor",
  "body": "When using valueAccessor='amount', tooltip displays 'undefined'.\n\ndiagnoseConfig output: ✓ no issues detected.",
  "labels": ["bug"]
}
→ Returns: Open this URL to submit the issue: https://github.com/nteract/semiotic/issues/new?...

CLI alternative

For quick validation without an MCP client:

npx semiotic-ai --doctor       # validate component + props JSON
npx semiotic-ai --schema       # dump all chart schemas
npx semiotic-ai --compact      # compact schema (fewer tokens)

Documentation

Interactive docs and examples

• Getting Started
• Charts — all 37 chart types with live examples
• Frames — full Frame API reference
• Features — axes, annotations, tooltips, styling, Vega-Lite translator
• Cookbook — advanced patterns and recipes
• Playground — interactive prop exploration

Upgrading

• Migration Guide — upgrading from v1.x or v2.x
• Changelog — full release history

Contributing

See CONTRIBUTING.md. Our community follows the nteract Code of Conduct.

Acknowledgments

Development of this library owes a lot to Susie Lu, Jason Reid, James Womack, Matt Herman, Shelby Sturgis, and Tristan Reid.

The Sankey layout engine is based on sankey-plus by Tom Shanley, which improved on his earlier d3-sankey-circular with better cycle detection, hierarchical arc stacking, and dynamic extent adjustment.

Semiotic icon based on an icon by Andre Schauer.

License

Apache 2.0