MetricUI

The missing UI layer for React dashboards.
KPI cards, charts, tables, and layout — with built-in formatting, theming, data states, and zero config.

Homepage · Docs · Analytics Demo · SaaS Demo · GitHub Demo · Wikipedia Live · MCP Server · Roadmap

Web Analytics · SaaS Metrics · GitHub Analytics · Wikipedia Live · World Explorer — all with AI Insights, cross-filtering, drill-downs, and export.

Install

npm install metricui

That's it. All chart dependencies are included.

CDN (no bundler needed)

For browser sandboxes, Claude artifacts, v0, Bolt, or anywhere without npm:

import { KpiCard, AreaChart, MetricProvider } from "https://cdn.jsdelivr.net/npm/metricui@latest/dist/metricui.browser.mjs";

<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/metricui@latest/dist/styles.css" />

Why MetricUI?

You're building a dashboard. You need KPI cards, charts, tables. You reach for Recharts + shadcn + custom CSS and spend days wiring up formatting, dark mode, loading states, and responsive layouts.

Stop assembling dashboards from parts.

import {
  Dashboard, DashboardHeader, PeriodSelector,
  MetricGrid, KpiCard, AreaChart, DonutChart, DataTable, Callout,
} from "metricui";
import "metricui/styles.css";

export default function App() {
  return (
    <Dashboard theme="emerald" filters={{ defaultPreset: "30d" }}>
      <DashboardHeader title="Revenue" lastUpdated={new Date()} actions={<PeriodSelector comparison />} />

        <MetricGrid>
          <MetricGrid.Section title="Key Metrics" />
          <KpiCard title="Revenue" value={127450} format="currency"
            comparison={{ value: 113500 }} comparisonLabel="vs last month"
            sparkline={{ data: [89, 94, 99, 103, 109, 114, 127], previousPeriod: [78, 82, 85, 88, 91, 95, 98] }}
            conditions={[
              { when: "above", value: 120000, color: "emerald" },
              { when: "below", value: 90000, color: "red" },
            ]}
          />
          <KpiCard title="Users" value={8420} format="compact"
            comparison={[{ value: 7680, label: "vs last month" }, { value: 6200, label: "vs last year" }]}
            highlight
          />
          <KpiCard title="Churn" value={3.2} format="percent"
            comparison={{ value: 3.7, invertTrend: true }}
            goal={{ value: 2.5, showTarget: true, showRemaining: true }}
          />

          <Callout value={12.3} rules={[
            { min: 10, variant: "success", title: "Strong Growth", message: "Revenue grew {value}% this month." },
            { max: 0, variant: "error", title: "Revenue Declined", message: "Revenue dropped {value}%." },
          ]} />

          <MetricGrid.Section title="Trends" border />
          <AreaChart data={revenueData} comparisonData={prevPeriod} format="currency" title="Revenue Trend"
            referenceLines={[{ axis: "y", value: 50000, label: "Target", style: "dashed" }]}
            thresholds={[{ from: 0, to: 30000, color: "#EF4444", opacity: 0.05 }]}
          />
          <DonutChart data={planBreakdown} format="currency" title="By Plan" centerValue="$127K" centerLabel="Total" />

          <MetricGrid.Section title="Details" border />
          <DataTable data={customers} title="Top Customers" columns={columns} searchable pageSize={10} />
        </MetricGrid>
    </Dashboard>
  );
}

Zero layout code. <Dashboard> wraps all providers (theme, filters, cross-filter, drill-down, linked hover) in one component. MetricGrid auto-detects component types — KPIs row up, charts pair, tables go full width. DashboardHeader shows live status with auto-ticking "Updated Xm ago". Responsive out of the box.

Features

AI Insights — Bring Your Own LLM

Drop <DashboardInsight /> into any dashboard. A floating chat button appears — click it, ask questions about your data. The AI auto-collects live data from every component, builds context-rich prompts, and streams analysis. Use @ to reference specific charts. Works with any LLM (OpenAI, Anthropic, local models). Docs →

<Dashboard ai={{ analyze: myLLM, company: "Acme Corp — B2B SaaS", context: "Q4 target: $500K" }}>
  <KpiCard title="Revenue" value={142800} aiContext="Primary metric. Enterprise drives 52%." />
  <DashboardInsight />
</Dashboard>

KPI Cards — Not Just Numbers

Sparkline with previous-period overlay. Goal progress bars. Conditional red/amber/green coloring. Multiple comparison badges. Copyable values. Drill-down links. Docs →

Headline Numbers on Any Chart

Every chart and table accepts a headline prop — a summary number in the card header that gives you the punchline at a glance.

<BarChart headline={{ value: 1200000, format: "currency", label: "Total" }} />
<BarChart headline="$1.2M total" />  // string shorthand

Supports formatting, comparison badges with trend arrows, and conditional coloring — same features as KpiCard, right in the chart header.

Charts with Reference Lines & Threshold Bands

Mark targets, benchmarks, and danger zones directly on charts. Comparison overlays show period-over-period trends as dashed lines. Works on AreaChart, LineChart, and BarChart.

<AreaChart
  data={revenueData}
  comparisonData={previousPeriod}
  referenceLines={[{ axis: "y", value: 50000, label: "Target", style: "dashed" }]}
  thresholds={[{ from: 0, to: 30000, color: "#EF4444", opacity: 0.05 }]}
  format="currency"
/>

Data-Driven Alerts

Pass a value and rules — Callout auto-selects the right variant, title, and message. Supports embedded formatted metrics, action buttons, collapsible detail, and auto-dismiss.

Expandable Data Tables

Click a row and a mini-dashboard slides open — sparklines, gauges, status indicators, badges. Plus search, multi-sort, pagination, pinned columns, 12 column types, and row conditions. Docs →

Conversion Funnels

Auto-computed stage-to-stage conversion rates. Vertical or horizontal. Smooth or linear interpolation. Docs →

Light & Dark Mode

Wikipedia live demo in light mode.

CSS variables. Zero config. Every component adapts automatically. Theming guide →

Smart Format Engine

One prop formats any value. Currency, percentages, durations, compact notation — with locale support. Docs →

<KpiCard value={127450} format="currency" />        // → $127.5K
<KpiCard value={4.2} format="percent" />             // → 4.2%
<KpiCard value={3725} format="duration" />           // → 1h 2m 5s
<KpiCard value={2400000} format="number" />          // → 2.4M

Theme Presets

One prop. Entire dashboard changes color. 8 built-in presets. Custom presets via ThemePreset type. Theming guide →

<Dashboard theme="emerald">   // Green accent + green-first chart palette
<Dashboard theme="rose">      // Pink accent + pink-first chart palette
<Dashboard theme="amber">     // Warm amber everything

MetricGrid — Zero Layout Code

Drop components in. It figures out the layout. Docs →

<MetricGrid>
  <MetricGrid.Section title="Overview" />
  <KpiCard ... />  <KpiCard ... />  <KpiCard ... />
  <AreaChart ... />          {/* Auto 2/3 width */}
  <DonutChart ... />         {/* Auto 1/3 width */}
  <DataTable ... />          {/* Auto full width */}
</MetricGrid>

Filter System

Complete filter context — wire PeriodSelector, DropdownFilter, SegmentToggle, and FilterTags together with zero boilerplate. Filtering guide →

<Dashboard theme="indigo" filters={{ defaultPreset: "30d" }}>
  <DashboardHeader title="Dashboard" actions={<PeriodSelector comparison />} />
  <SegmentToggle options={["All", "Enterprise", "SMB"]} field="segment" />
  <DropdownFilter label="Region" options={regions} field="region" multiple />
  <FilterTags />  {/* Auto-renders active filters as dismissible chips */}
</Dashboard>

Saved Views & Shareable Links

useDashboardState() captures the entire dashboard state (filters, period, dimensions, cross-filter) as a JSON-safe snapshot. Serialize to URL params for shareable links or persist to localStorage / your backend. Cookbook recipe →

Data States

Every component handles loading, empty, error, and stale states out of the box. Docs →

Error Boundaries

One chart crashes? The rest keep running. Dev mode shows component name + actionable hints. Prod mode shows clean retry UI.

Accessibility

prefers-reduced-motion, focus-visible rings, ARIA attributes on charts, keyboard-accessible drill-downs. Docs →

Components

Cards & Metrics

Charts

Layout

Filters

Status & Alerts

AI-First: MCP Server + llms.txt

Most component libraries give you docs and hope the AI figures it out. MetricUI gives the AI structured knowledge of every component, every prop, and every pattern — so it generates production-quality dashboards on the first try.

# One command. That's it.
claude mcp add --transport stdio metricui -- npx -y @metricui/mcp-server

The difference is real

Here's what happens when you prompt an AI with "Build me a SaaS dashboard with MRR, churn, users, and revenue breakdown":

// The AI guesses at library APIs, builds everything from scratch
import { LineChart, Line, XAxis, YAxis, PieChart, Pie } from "recharts";

export default function Dashboard() {
  return (
    <div className="p-8">
      <h1 className="text-2xl font-bold mb-6">SaaS Dashboard</h1>

      <div className="grid grid-cols-4 gap-4 mb-8">
        <div className="border rounded-lg p-4">
          <p className="text-sm text-gray-500">MRR</p>
          <p className="text-2xl font-bold">${(127450).toLocaleString()}</p>
          <p className="text-sm text-green-600">+12.3%</p>
        </div>
        <div className="border rounded-lg p-4">
          <p className="text-sm text-gray-500">Churn Rate</p>
          <p className="text-2xl font-bold">3.2%</p>
          <p className="text-sm text-green-600">-13.5%</p>
        </div>
        {/* ...more hand-built cards with no formatting engine, no sparklines,
            no conditional coloring, no goal tracking... */}
      </div>

      <LineChart width={800} height={300} data={data}>
        <XAxis dataKey="month" />
        <YAxis />
        <Line dataKey="revenue" stroke="#8884d8" />
        {/* No reference lines. No threshold bands. No comparison overlay.
            No dark mode. No loading states. No error boundaries. */}
      </LineChart>
    </div>
  );
}

import {
  Dashboard, DashboardHeader, PeriodSelector,
  MetricGrid, KpiCard, Callout, AreaChart, DonutChart, BarChart,
  DataTable, Badge,
} from "metricui";
import "metricui/styles.css";

export default function App() {
  return (
    <Dashboard theme="emerald" filters={{ defaultPreset: "30d" }}>
      <DashboardHeader
          title="SaaS Metrics"
          subtitle="Real-time metrics overview"
          lastUpdated={new Date()}
          actions={<PeriodSelector comparison />}
        />
        <MetricGrid>
          <MetricGrid.Section title="Key Metrics" />

          <KpiCard title="Monthly Revenue" value={127450} format="currency"
            comparison={{ value: 113500 }} comparisonLabel="vs last month"
            sparkline={{ data: [89, 94, 99, 103, 109, 114, 127],
              previousPeriod: [78, 82, 85, 88, 91, 95, 98], interactive: true }}
            conditions={[
              { when: "above", value: 115000, color: "emerald" },
              { when: "below", value: 90000, color: "red" },
            ]} />

          <KpiCard title="Churn Rate" value={3.2} format="percent"
            comparison={{ value: 3.7, invertTrend: true }}
            goal={{ value: 2.5, showTarget: true, showRemaining: true }}
            conditions={[
              { when: "below", value: 2.5, color: "emerald" },
              { when: "above", value: 4, color: "red" },
            ]} />

          <KpiCard title="Active Users" value={8420} format="number"
            comparison={{ value: 7680 }} copyable
            drillDown={true} />

          <KpiCard title="Conversion" value={4.8} format="percent"
            comparison={{ value: 4.2 }}
            sparkline={{ data: [3.1, 3.4, 3.8, 4.0, 4.1, 4.2, 4.8] }} />

          <Callout value={12.3} rules={[
            { min: 15, variant: "success", title: "Exceptional Growth",
              message: "Revenue grew {value}% — exceeding target by 50%." },
            { min: 5, max: 15, variant: "info", title: "Healthy Growth",
              message: "Revenue grew {value}% month-over-month." },
            { max: 0, variant: "error", title: "Revenue Declined",
              message: "Revenue dropped {value}%." },
          ]} action={{ label: "View growth report", onClick: () => {} }} />

          <MetricGrid.Section title="Trends" subtitle="Last 30 days" border />

          <AreaChart data={revenueData} comparisonData={comparisonData}
            format="currency" title="Revenue Trend"
            referenceLines={[{ axis: "y", value: 50000, label: "Target",
              color: "#10B981", style: "dashed" }]}
            thresholds={[{ from: 0, to: 40000, color: "#EF4444", opacity: 0.05 }]}
            xAxisLabel="Month" yAxisLabel="Revenue ($)"
            height={360} legend />

          <DonutChart data={breakdownData} format="currency"
            title="Revenue by Plan" centerValue="$99.4K" centerLabel="Total MRR" />

          <MetricGrid.Item span="full">
            <BarChart preset="grouped" data={channelData}
              keys={["revenue", "conversions"]} indexBy="channel"
              sort="desc" format="currency" title="Channel Performance" legend />
          </MetricGrid.Item>

          <MetricGrid.Section title="Details" border />
          <DataTable data={tableData} title="Top Customers" searchable
            columns={[
              { key: "name", header: "Customer", sortable: true },
              { key: "plan", header: "Plan",
                render: (v) => <Badge variant={v === "Enterprise" ? "info" : "default"}>{String(v)}</Badge> },
              { key: "mrr", header: "MRR", format: "currency", sortable: true },
              { key: "status", header: "Status",
                render: (v) => <Badge variant={v === "active" ? "success" : v === "at-risk" ? "warning" : "danger"}>{String(v)}</Badge> },
            ]} />
        </MetricGrid>
    </Dashboard>
  );
}

Same prompt. The AI with MetricUI MCP generates:

• DashboardHeader with live status + auto-ticking "Updated Xm ago"
• Dashboard wrapper with filters, cross-filtering, and comparison toggle
• MetricGrid auto-layout (zero CSS)
• KpiCards with conditional coloring, goal progress bars, sparkline overlays, drill-down links
• AreaChart with dashed target reference line, danger zone threshold band, and previous-period comparison overlay
• Data-driven Callout that auto-picks severity from a growth number
• Sorted grouped BarChart, DonutChart with center KPI
• Searchable DataTable with Badge status columns
• Theme preset, dark mode, animations, error boundaries — all automatic

The AI doesn't guess. It knows. 13 tools, 26 components, every prop, every pattern. Full MCP Server docs →

llms.txt

Machine-readable documentation for AI models at /llms.txt. Every component, every prop, every type, every pattern — so even AI tools without MCP support can generate correct MetricUI code.

Roadmap

MetricUI is building toward 1.0 — cross-filtering, zero-config charts, anomaly detection, data stories, and a stable API you can build on with confidence. See what's shipped, what's next, and where we're headed:

View the full roadmap →

Built With

• Nivo — chart rendering (line, bar, pie, heatmap)
• Tailwind CSS — styling (ships pre-built, Tailwind not required in your project)
• Lucide — icons
• React 18/19

License

MIT

Built for developers who care about design.