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io.github.ganapativs/microcharts MCP Server

io.github.ganapativs/microcharts

106 tiny React charts for AI—word-sized, zero dependencies, generated alt text, and MCP-ready.

What is the io.github.ganapativs/microcharts MCP server?

The microcharts MCP server exposes a library of 106 handcrafted, lightweight React chart types designed for AI-native use. It provides tools to find the right chart type, retrieve its props and samples, and render charts to self-contained SVG with auto-generated accessible descriptions. Charts are ~2–7 kB interactive and ~1–4 kB static, with zero runtime dependencies and server-component safety.

microcharts is a collection of word-sized charts built to sit inside interfaces—sentences, table cells, KPI cards, and streamed AI replies. The MCP server lets Claude, Cursor, and other AI agents discover, configure, and render charts programmatically. Every chart is plain data plus a generated natural-language summary, making it safe for an LLM to emit mid-conversation and for humans to read and verify.

How to install io.github.ganapativs/microcharts

Copy-paste configuration for popular MCP clients.

transport: stdio
Config generated by PluginBench — verify against the source before use.
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "microcharts": {
      "command": "npx",
      "args": [
        "-y",
        "@microcharts/mcp"
      ]
    }
  }
}

Tools & capabilities

Tools this server exposes to the agent.

  • find — Discover the chart type that answers a specific question from the 106-chart catalog.
  • get — Retrieve exact props, data shape, and a ready-to-render sample for a given chart type.
  • render — Render a chart to a self-contained SVG with auto-generated alt text and accessible name.

Use cases

  • Generate inline charts in AI chat replies with auto-generated alt text for accessibility.
  • Programmatically select the best chart type for a data question and render it instantly.
  • Create lightweight, interactive charts in React apps with zero external dependencies.
  • Embed charts in server components with zero client-side JavaScript overhead.
  • Build themed, motion-enabled charts with keyboard navigation and screen-reader support.

io.github.ganapativs/microcharts MCP server FAQ

What is the microcharts MCP server?

It's a Model Context Protocol server that gives AI assistants (Claude, Cursor, etc.) three tools: find the right chart type for a question, get its props and sample data, and render it to SVG with auto-generated alt text.

Is it free?

Yes. microcharts is MIT-licensed open source. The MCP server runs locally on your machine over stdio—nothing is hosted and no API key is required.

How do I install it in Cursor or Claude Desktop?

Add it to your MCP servers config: `{"mcpServers": {"microcharts": {"command": "npx", "args": ["-y", "@microcharts/mcp"]}}}`

Does it require authentication?

No. The server runs entirely on your machine and has no external dependencies or API calls.

What chart types are available?

106 stable chart types across four groups: 34 core (sparklines, bars, deltas), 26 decision (funnels, bumps), 23 expressive (confidence bands, calendars), and 23 frontier charts. Browse the full catalog at microcharts.dev/docs/charts.

Can I use these charts in my React app?

Yes. Install `@microcharts/react` from npm. Charts are zero-dependency, server-component safe, and ship per-component subpaths so you only pay for what you use.

README (reference)

Source of truth, from the repository.

<div align="center"> <img src="assets/promo.png" alt="microcharts — word-sized charts for React, made for AI first and for the people reading what it writes. 106 chart types, zero dependencies, ~2–7 kB interactive · ~1–4 kB static." width="920">

@microcharts/react

Word-sized charts for React — zero runtime dependencies, ~2–7 kB interactive · ~1–4 kB static, accessible by default, and server-component safe.

<br>

npm gzip per chart zero dependencies types React 18 · 19 MIT Reviewed with Argos

Docs · Gallery · Quickstart · AI usage · llms.txt

</div>

microcharts is 106 tiny, handcrafted chart types built to sit inside an interface: a sentence, a table cell, a KPI card, a tab header, a streamed AI reply. The grammar is small enough for a model to emit correctly mid-sentence, and every chart describes itself in words, so a chart an LLM streams into a chat reply is one a person can read and check.

Status: tested and in production use, but not across every stack and edge yet. If you hit something, open an issue on GitHub.

Why

  • AI-native. A chart is plain data plus a generated sentence. One grammar across all 106 types — a model that has seen one chart can write them all. → AI usage
  • Zero dependencies. No chart engine, no D3 — just SVG. React is the only peer. CI-enforced, forever.
  • Server-component safe. Static charts are hook-free and render to HTML with zero client JavaScript. Interactivity is a separate opt-in /interactive import.
  • Accessible by default. Every chart is an img with a natural-language summary built from your data; it updates when the numbers do. → Accessibility
  • Tiny. ~2–7 kB interactive · ~1–4 kB static gzip per chart, budget-gated in CI. Every type has one documented, honest encoding channel and a stated precision.
  • Motion, opt-in. Interactive charts draw on with animate plus one import "@microcharts/react/motion", and glide continuous marks when data updates. Entrances respect prefers-reduced-motion and never replay over server-rendered HTML. → Motion

Install

npm install @microcharts/react

Import the stylesheet once at the root of your app — it carries every theming token and chart style in a low-specificity cascade layer, so your own styles always win:

// app/layout.tsx
import "@microcharts/react/styles.css";

Your first chart

Every chart renders from data alone. This works in a React Server Component with zero client JavaScript — pure SVG, and its accessible name is generated from the data.

import { Sparkline } from "@microcharts/react/sparkline";

<Sparkline data={[3, 5, 4, 8, 6, 9]} title="Weekly revenue" />;

Each chart imports from its own subpath, so you only ship what you use. Every chart follows the same two-entry pattern: a static default, and an /interactive twin.

Add interactivity

Need hover, keyboard navigation, touch, or live announcements? Import the same chart from /interactive. The rendered output and the accessible name are identical, because the interactive entry composes its static twin. It only adds props; you opt into the client component where it matters.

import { Sparkline } from "@microcharts/react/sparkline/interactive";

<Sparkline data={[3, 5, 4, 8, 6, 9]} title="Weekly revenue" />;

Every interactive chart shares one contract, so you learn it once. Hover or arrow keys make a unit active; a click, tap, <kbd>Enter</kbd>, or <kbd>Space</kbd> selects it and pins the readout so it survives blur; <kbd>Escape</kbd> or a press outside the chart clears; <kbd>Home</kbd>/<kbd>End</kbd> jump to the ends. Read it back with onActive and onSelect — payload { index, value, label?, formatted? }, where value is the raw number and formatted is the chart's ready-to-display string — and control the pin with selectedIndex / defaultSelectedIndex. Set readout={false} to hide the in-chart value chip and render datum.formatted wherever you like. Single-unit scalar charts (Delta, Progress, StatusDot, Bullet, …) take onSelect alone.

<Sparkline data={[3, 5, 4, 8, 6, 9]} onActive={(d) => setHovered(d?.value ?? null)} onSelect={(d) => pin(d)} />

Annotate with children

Thresholds, markers, and target zones are children — the same grammar on every chart that supports them:

import { Sparkline } from "@microcharts/react/sparkline";
import { Threshold, Marker } from "@microcharts/react/annotations";

<Sparkline data={[120, 180, 240, 210, 260]} title="Latency p95">
  <Threshold y={200} label="SLO" />
  <Marker x={2} celebrate />
</Sparkline>;

Theme it

About two dozen --mc-* CSS custom properties are the runtime contract; presets are token bundles. Set one on a subtree with the provider — presets are visual only and never change what the data means:

import { MicroProvider } from "@microcharts/react";

<MicroProvider theme="editorial">
  <Sparkline data={[3, 5, 4, 8, 6, 9]} />
</MicroProvider>;

Presets: modern (default), editorial, mono, vivid, plus output-context print and eink. Dark mode is hand-tuned, not inverted. For a whole brand theme, defineTheme (from @microcharts/react/theme) derives a matched, color-blind-safe palette and dark twins from one accent:

import { defineTheme } from "@microcharts/react/theme";

const brand = defineTheme({ accent: "#6d28d9" });
<MicroProvider style={brand.style}>…</MicroProvider>;

Retune density with one scalar (--mc-density), give figures their own face (--mc-font-numeric), or recolor a single categorical chart with a colors array. → Theming guide

The catalog

106 stable chart types — 34 core, 26 decision, 23 expressive, 23 frontier — grouped by the question each one answers. data alone always renders something correct, and a prop name means the same thing on every chart (domain, color, title, summary, label, format…), so picking a chart is picking the question you need answered.

Sparklines, bars, deltas, and bullets through bump charts, funnels, honeycombs, calendar strips, and confidence bands — browse them all in the live gallery →

Not shipping, on purpose: pie, needle-gauge/speedometer, battery, waffle, violin. Each fails at micro scale or on the honest-encoding bar, and each has an in-catalog replacement (Bullet for gauges, SegmentedBar for pie, MicroBox for violin). → what to use instead

Made for models

A model writes the chart; a person reads it. The docs site publishes machine surfaces alongside the human ones:

SurfaceWhat it is
/llms.txtCurated map of the catalog and guides
/llms-full.txtThe complete generated docs corpus
/catalog.jsonEvery chart's name, import path, props, data shapes

The MCP server

The surfaces above are for reading. @microcharts/mcp lets an assistant call the library directly: a Model Context Protocol server that runs on your machine over stdio, with three tools backed by this library — find the chart type that answers a question, get its exact props and a ready-to-render sample, and render it to a self-contained SVG with the generated alt text attached.

{
  "mcpServers": {
    "microcharts": {
      "command": "npx",
      "args": ["-y", "@microcharts/mcp"]
    }
  }
}

Works in Claude Desktop, Claude Code, Cursor, and VS Code; nothing is hosted and no key is involved. The same three capabilities ship as Vercel AI SDK tools on the @microcharts/mcp/ai-sdk subpath. Full reference: microcharts.dev/docs/mcp. Also listed in the Glama MCP registry.

Compatibility

React 18 and 19. ESM-only, per-component subpath exports, types-first export conditions. Static charts render in any RSC or SSR setup with no client runtime.

sideEffects is a two-entry allowlist, never false: styles.css and the opt-in ./motion engine are both imported for their side effects, and false would let a bundler drop them. Every other module is side-effect free and tree-shakes normally, and since charts ship as per-component subpaths, you only pay for the ones you import.

Contributing

pnpm install
pnpm check     # typecheck + lint + format + test + knip
pnpm size      # gzip budgets (needs a build first)
pnpm build

Bug fixes and fixes to existing charts are the most useful thing to send. New props and new chart types are open but held to a high bar — the catalog is already broad at 106 types, so a new one needs a question the others can't answer. Either way, open an issue and wait for a yes before you open a PR. CONTRIBUTING.md has the policy, the CI gates, and what a good bug report contains.

License

MIT © Ganapati V S

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