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Create interactive visualizations and query data sources (SQLite, CSV, Parquet, JSON)
Create interactive visualizations and query data sources (SQLite, CSV, Parquet, JSON)
Valid MCP server (2 strong, 4 medium validity signals). 3 known CVEs in dependencies (0 critical, 2 high severity) Package registry verified. Imported from the Official MCP Registry.
9 files analyzed ยท 4 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
This plugin requests these system permissions. Most are normal for its category.
Add this to your MCP configuration file:
{
"mcpServers": {
"mcp-server": {
"args": [
"-y",
"@gluip/chart-canvas-mcp"
],
"command": "npx"
}
}
}From the project's GitHub README.
Interactive visualization dashboard for AI assistants via Model Context Protocol
Create beautiful charts, diagrams, and tables directly from your AI conversations. Chart Canvas provides a real-time dashboard that displays visualizations as you work with LLMs like Claude.
Watch the full demo on YouTube to see Chart Canvas in action!
โจ Multiple Chart Types: Line, bar, scatter, pie charts, tables, and Mermaid diagrams
๐จ Interactive Dashboard: Drag-and-drop grid layout with real-time updates
๐ Live Synchronization: Changes appear instantly in your browser
๐ Rich Visualizations: Powered by ECharts and Mermaid
๐พ Universal Data Sources: Query SQLite, CSV, Parquet, JSON, and NDJSON files directly
โก Smart Data Flow: Execute queries server-side - data stays local, never sent to LLM
๐ Privacy First: Your data never leaves your machine
๐ Easy Setup: One command to get started
๐ Production Ready: Built-in production mode with optimized builds
Chart Canvas can query and visualize data from multiple file formats:
.db, .sqlite, .sqlite3) - Relational databases.csv) - Comma-separated values.parquet) - Columnar storage format.json) - JSON arrays of objects.jsonl, .ndjson) - Newline-delimited JSONPrivacy & Performance: All queries execute locally on your machine using DuckDB. Query results are transformed into visualizations server-side - only metadata (chart configuration) is sent to the LLM, never your actual data. This makes it fast, scalable, and private.
npm install -g @gluip/chart-canvas-mcp
Or use directly with npx (no installation needed):
npx @gluip/chart-canvas-mcp
Add to your MCP client configuration (e.g., Claude Desktop):
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%/Claude/claude_desktop_config.json
{
"mcpServers": {
"chart-canvas": {
"command": "npx",
"args": ["-y", "@gluip/chart-canvas-mcp"]
}
}
}
showCanvas tool to open the dashboard in your browser"Show me a line chart comparing sales data for 2023 and 2024"
"Create a pie chart showing market share by region"
"Draw a flowchart for the user authentication process"
"Make a table with team member information"
"Show me the database schema for my SQLite database"
"Query the athletes table and show the top 10 with most personal records"
"Create a chart showing sales trends from the database grouped by region"
Create charts, diagrams, and tables on the canvas.
Supported Types:
line - Line charts with multiple seriesbar - Bar charts for comparisonsscatter - Scatter plots for data distributionpie - Pie charts with labelstable - Data tables with headersflowchart - Mermaid diagrams (flowcharts, sequence diagrams, Gantt charts, etc.)Example:
{
type: "line",
title: "Monthly Sales",
series: [
{ name: "2023", data: [[1, 120], [2, 132], [3, 101]] },
{ name: "2024", data: [[1, 220], [2, 182], [3, 191]] }
],
xLabels: ["Jan", "Feb", "Mar"]
}
Remove a specific visualization by ID.
Remove all visualizations from the canvas.
Open the dashboard in your default browser.
Inspect the structure of a SQLite database to understand available tables and columns before writing queries.
Parameters:
databasePath - Path to SQLite database file (e.g., ./data/mydb.sqlite or absolute path)Example:
{
databasePath: "/path/to/database.db";
}
Returns: Formatted schema showing all tables, columns, data types, and constraints.
Execute a SQL query on a SQLite database and create a visualization from the results. Queries are executed server-side and must be read-only (SELECT only). Maximum 10,000 rows.
Parameters:
databasePath - Path to SQLite database filequery - SQL SELECT query (read-only)visualizationType - Type of chart: line, bar, scatter, pie, or tablecolumnMapping (optional for table) - Mapping of columns to chart axes:
xColumn - Column for X-axis (required for charts)yColumns - Array of columns for Y-axis (required for charts)seriesColumn - Column to group data into separate series (optional)groupByColumn - Alternative grouping column (optional)title - Optional title for visualizationdescription - Optional descriptionuseColumnAsXLabel - If true, use X column values as labels instead of numbersExample:
{
databasePath: "./data/sales.db",
query: "SELECT region, SUM(revenue) as total FROM sales GROUP BY region",
visualizationType: "bar",
columnMapping: {
xColumn: "region",
yColumns: ["total"]
},
title: "Revenue by Region",
useColumnAsXLabel: true
}
Security: Only SELECT and WITH (CTE) queries are allowed. INSERT, UPDATE, DELETE, DROP, and other modifying operations are blocked.
# Clone repository
git clone https://github.com/gluip/chart-canvas.git
cd chart-canvas
# Install backend dependencies
cd backend
npm install
# Install frontend dependencies
cd ../frontend
npm install
# Development mode (backend + frontend separate)
# Terminal 1 - Backend
cd backend
npm run dev
# Terminal 2 - Frontend
cd frontend
npm run dev
# Production mode (single server)
cd backend
npm run build:all
npm run start:prod
{
"mcpServers": {
"chart-canvas": {
"command": "/path/to/node",
"args": [
"/path/to/chart-canvas/backend/node_modules/.bin/tsx",
"/path/to/chart-canvas/backend/src/index.ts"
]
}
}
}
MIT ยฉ 2026 Martijn
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