chuk-mcp-chart 1.0.1

MCP server for interactive data visualisation — bar, pie, line, doughnut, radar, polar, and area charts

Chuk MCP Chart

Interactive data visualisation via MCP — paste a CSV, describe your data, ask for a chart. Bar, pie, line, doughnut, radar, polar, and area charts rendered instantly.

This is a demonstration project provided as-is for learning and testing purposes.

Features

Three tools that turn raw data into beautiful charts:

1. Show Chart (show_chart)

Create a chart from explicit data. Provide labels, one or more datasets, and optional configuration:

• Chart types: bar, line, pie, doughnut, radar, polar, area
• Axis labels, legend position, stacked mode
• Custom colours per dataset
• Auto-assigned colour-blind-friendly palette

2. Chart from CSV (chart_from_csv)

Paste raw CSV text and get a chart — zero configuration required:

• First non-numeric column becomes category labels
• Every numeric column becomes a dataset (series)
• If all columns are numeric, row numbers are used as labels
• Perfect for spreadsheet data

3. Chart from JSON (chart_from_json)

Pass a JSON array of objects and get a chart automatically:

• First string field becomes category labels
• Every numeric field becomes a dataset
• Great for API responses or structured data

Installation

Using uvx (Recommended - No Installation Required!)

uvx chuk-mcp-chart

This automatically downloads and runs the latest version. Perfect for Claude Desktop!

Using uv (Recommended for Development)

# Install from PyPI
uv pip install chuk-mcp-chart

# Or clone and install from source
git clone https://github.com/chrishayuk/chuk-mcp-chart.git
cd chuk-mcp-chart
uv sync --dev

Using pip (Traditional)

pip install chuk-mcp-chart

Usage

With Claude Desktop

Option 1: Use the Public Server (Easiest)

Connect to the hosted public server at chart.chukai.io:

MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "chart": {
      "url": "https://chart.chukai.io/mcp"
    }
  }
}

Option 2: Run Locally with uvx

{
  "mcpServers": {
    "chart": {
      "command": "uvx",
      "args": ["chuk-mcp-chart"]
    }
  }
}

Option 3: Run Locally with pip

{
  "mcpServers": {
    "chart": {
      "command": "chuk-mcp-chart"
    }
  }
}

Standalone

# With uvx (recommended - always latest version)
uvx chuk-mcp-chart

# With uvx in HTTP mode
uvx chuk-mcp-chart http

# Or if installed locally
chuk-mcp-chart
chuk-mcp-chart http

Or with uv/Python:

# STDIO mode (default, for MCP clients)
uv run chuk-mcp-chart
# or: python -m chuk_mcp_chart.server

# HTTP mode (for web access)
uv run chuk-mcp-chart http
# or: python -m chuk_mcp_chart.server http

STDIO mode is for MCP clients like Claude Desktop and mcp-cli. HTTP mode runs a web server on http://localhost:8000 for HTTP-based MCP clients.

Example Prompts

Once configured, try asking:

• "Chart my monthly expenses" (then paste your data)
• "Show Python vs JavaScript popularity as a pie chart"
• "Turn this CSV into a line chart showing trends over time"
• "Create a bar chart of Q1-Q4 revenue: 42000, 51000, 48000, 55000"
• "Show a radar chart comparing three products across speed, quality, and price"
• "Make a doughnut chart of browser market share"

Tool Reference

show_chart

Create a chart from explicit labels and datasets.

Parameters:

Parameter	Type	Default	Description
chart_type	string	"bar"	One of: bar, line, pie, doughnut, radar, polar, area
title	string	"Chart"	Chart title
labels	string	—	Comma-separated category labels (e.g. "Jan,Feb,Mar")
datasets	string	—	JSON array of dataset objects (see below)
x_axis_label	string	—	X axis label
y_axis_label	string	—	Y axis label
legend_position	string	—	Legend position: top, bottom, left, right, none
stacked	bool	false	Stack bar/area datasets

Dataset format (JSON string):

[
  {"label": "Revenue", "values": [12, 19, 3, 5, 2, 3]},
  {"label": "Expenses", "values": [8, 14, 2, 4, 1, 2], "color": "#ef4444"}
]

chart_from_csv

Parse CSV text into a chart automatically.

Parameters:

Parameter	Type	Default	Description
csv_data	string	—	Raw CSV text with header row
chart_type	string	"bar"	Chart type
title	string	"Chart"	Chart title

Example input:

Month,Revenue,Expenses
Jan,4200,3800
Feb,5100,4200
Mar,4800,4100

chart_from_json

Parse a JSON array into a chart automatically.

Parameters:

Parameter	Type	Default	Description
json_data	string	—	JSON array of objects
chart_type	string	"bar"	Chart type
title	string	"Chart"	Chart title

Example input:

[
  {"language": "Python", "popularity": 28.1},
  {"language": "JavaScript", "popularity": 21.3},
  {"language": "TypeScript", "popularity": 12.7}
]

Development

Setup

# Clone the repository
git clone https://github.com/chrishayuk/chuk-mcp-chart.git
cd chuk-mcp-chart

# Install with uv (recommended)
uv sync --dev

# Or with pip
pip install -e ".[dev]"

Running Tests

make test              # Run tests
make test-cov          # Run tests with coverage
make coverage-report   # Show coverage report

Code Quality

make lint      # Run linters
make format    # Auto-format code
make typecheck # Run type checking
make security  # Run security checks
make check     # Run all checks

Building

make build         # Build package
make docker-build  # Build Docker image

Deployment

Fly.io

Deploy to Fly.io with a single command:

# First time setup
fly launch

# Deploy updates
fly deploy

The server will be available via HTTP at your Fly.io URL.

Docker

# Build the image
docker build -t chuk-mcp-chart .

# Run the container
docker run -p 8000:8000 chuk-mcp-chart

Architecture

Built on top of chuk-mcp-server with chart rendering via chuk-view-schemas:

• Decorator-driven: Tools defined with @chart_tool — handles view metadata, structured content, and text fallback automatically
• Type-safe: All chart data uses Pydantic v2 models (ChartContent, ChartDataset, AxisConfig, LegendConfig)
• Smart parsing: CSV and JSON tools auto-detect labels vs data columns
• Async native: All tools are async for optimal performance
• Dual transport: STDIO for MCP clients, HTTP for web access

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

Apache License 2.0 - See LICENSE file for details.

Acknowledgments

• Chart.js for the chart rendering engine
• chuk-mcp-server for the MCP framework
• Model Context Protocol for the MCP specification
• Anthropic for Claude and MCP support