# ChartPane

**Category:** 📊 Data Visualization  
**Repository:** https://github.com/ahmadsl/chartpane  
**Views:** 0  
**Installs:** 0  
**Upvotes:** 0  
**Directory Page:** https://allmcps.com/mcp/chartpane

## Description
Renders interactive Chart.js charts and dashboards inline in AI conversations.

## Claude Desktop Quick Installation
Heuristic fallback — verify the package name and runner against the repository README before running it. Uses `npx` (confidence: low):

```json
"mcpServers": {
  "chartpane": {
    "command": "npx",
    "args": ["-y","chartpane"]
  }
}
```

## Documentation & README

# ChartPane

MCP App that renders interactive Chart.js charts inline in Claude's UI. Works with Claude Desktop, ChatGPT, VS Code, Cursor, and any client that supports MCP Apps.

**Live instance:** [mcp.chartpane.com](https://mcp.chartpane.com/mcp)

## Features

- 9 chart types: bar, line, area, pie, doughnut, polarArea, bubble, scatter, radar
- Stacked and horizontal bar chart variants
- Multi-chart dashboard grids (up to 4 columns)
- Custom colors or automatic 12-color palette
- Client-side rendering — chart data never stored server-side
- Works with any MCP-compatible client (Claude Desktop, ChatGPT, VS Code, Cursor)

## Tools

- **`render_chart`** — Render a single chart (bar, line, area, pie, doughnut, polarArea, bubble, scatter, radar, stacked)
- **`render_dashboard`** — Render a multi-chart grid layout

## Quick Start

Add ChartPane to Claude Desktop via **Settings > Connectors > Add custom connector**:

```
https://mcp.chartpane.com/mcp
```

Or use `mcp-remote` (requires Node.js):

```json
{
  "mcpServers": {
    "chartpane": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://mcp.chartpane.com/mcp"]
    }
  }
}
```

## Usage Examples

### 1. Bar chart

**Prompt:** "Create a bar chart of quarterly revenue: Q1 $50k, Q2 $80k, Q3 $120k, Q4 $95k"

Claude calls `render_chart` with:

```json
{
  "type": "bar",
  "title": "Quarterly Revenue",
  "data": {
    "labels": ["Q1", "Q2", "Q3", "Q4"],
    "datasets": [{ "label": "Revenue ($k)", "data": [50, 80, 120, 95] }]
  }
}
```

An interactive bar chart renders inline in the conversation.

### 2. Pie chart

**Prompt:** "Show browser market share as a pie chart: Chrome 65%, Safari 19%, Firefox 8%, Edge 5%, Other 3%"

Claude calls `render_chart` with:

```json
{
  "type": "pie",
  "title": "Browser Market Share",
  "data": {
    "labels": ["Chrome", "Safari", "Firefox", "Edge", "Other"],
    "datasets": [{ "label": "Share", "data": [65, 19, 8, 5, 3] }]
  }
}
```

Each slice gets a distinct color from the built-in palette.

### 3. Multi-chart dashboard

**Prompt:** "Build a dashboard with monthly active users as a line chart and signups by channel as a bar chart"

Claude calls `render_dashboard` with:

```json
{
  "title": "Growth Dashboard",
  "charts": [
    {
      "type": "line",
      "title": "Monthly Active Users",
      "data": {
        "labels": ["Jan", "Feb", "Mar", "Apr", "May", "Jun"],
        "datasets": [{ "label": "MAU", "data": [12000, 15000, 18000, 22000, 28000, 35000] }]
      }
    },
    {
      "type": "bar",
      "title": "Signups by Channel",
      "data": {
        "labels": ["Organic", "Referral", "Paid", "Social"],
        "datasets": [{ "label": "Signups", "data": [4500, 3200, 2800, 1500] }]
      }
    }
  ],
  "columns": 2
}
```

Both charts render side-by-side in a grid layout.

## Self-Hosting

ChartPane runs on Cloudflare Workers.

```bash
npm install
cp .dev.vars.example .dev.vars    # Configure secrets (optional)
npm run dev                        # Local dev server (port 8787 + sandbox on 3456)
npm run deploy                     # Deploy to Cloudflare Workers
```

You'll need to create your own KV namespace and D1 database — see comments in `wrangler.jsonc`.

## Development

```bash
npm run dev        # wrangler dev + sandbox dev server (localhost:3456)
npm run build      # Type-check (tsc --noEmit) + bundle UI
npm test           # Run all tests (vitest)
npm run test:watch # Watch mode
```

## Architecture

Claude tool calls flow through a thin MCP server that validates input and returns `structuredContent`. The browser-side UI transforms input into Chart.js configs and renders to canvas. All shared logic (types, validation, colors, config) lives in `shared/`.

```
Claude tool call → server.ts (validate) → structuredContent
    → mcp-app.ts (browser) → buildChartConfig() → Chart.js canvas
```

## Privacy

ChartPane logs only request metadata (chart type, title, timestamp). Chart data values are never stored. Charts render entirely client-side in your browser. Full policy: [chartpane.com/privacy](https://chartpane.com/privacy)

## Support

- GitHub Issues: [github.com/ahmadnassri/chartpane/issues](https://github.com/ahmadnassri/chartpane/issues)
- Email: [support@chartpane.com](mailto:support@chartpane.com)

## License

MIT