ChartPane
Renders interactive Chart.js charts and dashboards inline in AI conversations.
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
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):
{
"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 $95k"
Claude calls render_chart with:
{
"type": "bar",
"title": "Quarterly Revenue",
"data": {
"labels": ["Q1", "Q2", "Q3", "Q4"],
"datasets": [{ "label": "Revenue ($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:
{
"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:
{
"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.
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
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
Support
- GitHub Issues: github.com/ahmadnassri/chartpane/issues
- Email: [email protected]
License
MIT
関連サーバー
Time MCP Server
Provides the current time using IANA timezone names, with automatic system timezone detection.
GoHighLevel
Integrate GoHighLevel with AI assistants like Claude and ChatGPT using a private API key.
esa
An MCP server for interacting with the esa.io knowledge-sharing platform.
stakeholder-mcp
Let your AI agent have conversations with different personas on features and implementation details
Notebooklm mcp server
Let your AI agents chat directly with Google NotebookLM for zero-hallucination answers.
n8n MCP Server
Provides workflow validation and best practices tools for the n8n automation platform.
Qonto
Interact with the Qonto Business API to manage finances, transactions, and account information using API credentials.
Odoo
Integrate Odoo with Large Language Models (LLMs) for enhanced business process automation.
Signbee
Document signing for AI agents. Send contracts for e-signature via MCP with email OTP verification and SHA-256 signing certificates.
Obsidian via REST
Access and manage your Obsidian vault through a local REST API.