Watsonx Visualization MCP Server

Watsonx Visualization MCP Server

Provides automated data visualization and analysis tools that intelligently select from over 40 chart types based on data structure and patterns. It enables users to generate statistical insights, interactive dashboards, and professional reports in HTML, PNG, and Word formats.

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Watsonx Visualization MCP Server

A comprehensive Model Context Protocol (MCP) server for automated data visualization and analysis, designed for seamless integration with IBM Watsonx Orchestrate.

🎯 Overview

This MCP server provides intelligent data visualization tools that automatically:

  • Select the most appropriate chart type based on data structure
  • Generate comprehensive data analysis and insights
  • Create visualizations in multiple formats (HTML, PNG, Word)
  • Support 40+ chart types including advanced visualizations
  • Provide statistical analysis, trend detection, and recommendations

✨ Features

Intelligent Chart Selection

Automatically determines the best visualization type based on:

  • Data structure and dimensions
  • Temporal patterns
  • Hierarchical relationships
  • Statistical distributions
  • Correlation patterns

Supported Chart Types

  • Basic: bar, column, line, area, pie
  • Stacked: stacked bar, stacked column
  • Statistical: boxplot, scatter, bubble, heatmap
  • Hierarchical: sunburst, tree map, hierarchy bubble, packed bubble
  • Temporal: line, area, dual axes lines, dual axes column
  • Specialized: waterfall, gantt chart, radar, wordcloud, network, tornado
  • KPI: kpi, bullet
  • Tabular: table, crosstab
  • Geographic: map, legacy map
  • Advanced: marimekko, radial, spiral, decision tree

Comprehensive Analysis

  • Statistical measures (mean, median, std dev, quartiles, etc.)
  • Trend detection and forecasting indicators
  • Correlation analysis
  • Outlier detection
  • Pattern recognition
  • Actionable recommendations

Multiple Output Formats

  • HTML: Interactive, responsive visualizations
  • PNG: High-quality static images
  • Word: Professional documents with analysis

🚀 Quick Start

Prerequisites

  • Node.js 18+
  • npm or yarn
  • IBM Watsonx Orchestrate account

Installation

Note: The package is not yet published on npm. Use local installation:

  1. Clone the repository:
git clone https://github.com/tdognin/watsonx-visualization-mcp.git
cd watsonx-visualization-mcp
  1. Install dependencies:
npm install
  1. Run tests to verify installation:
npm test
  1. Start the MCP server:
npm start

📖 Detailed installation guide: INSTALLATION_LOCALE.md

🔧 Configuration

MCP Server Configuration

The MCP server needs to be configured in your system configuration file (not in this project).

📖 For detailed step-by-step instructions, see GUIDE_CONFIGURATION_MCP.md

Quick configuration example for ~/.config/mcp/settings.json:

{
  "mcpServers": {
    "watsonx-visualization": {
      "command": "node",
      "args": ["/FULL/PATH/TO/watsonx-visualization-mcp/src/mcp-server/index.js"],
      "env": {}
    }
  }
}

⚠️ Important: Replace /FULL/PATH/TO/ with the actual path to your project directory.

Watsonx Orchestrate Integration

🚀 Quick Setup Guide: SETUP_WATSONX_ORCHESTRATE.md - Step-by-step guide to connect your local MCP server to Watsonx Orchestrate

📖 Complete Documentation: WATSONX_INTEGRATION.md - Detailed integration guide with advanced options

📖 Usage

Tool 1: generate_visualization

Generate a single visualization with automatic chart type selection and analysis.

Parameters:

  • data (required): JSON data to visualize
  • chartType (optional): Specific chart type (auto-selected if not provided)
  • outputFormat (optional): 'html', 'png', or 'word' (default: 'html')
  • includeAnalysis (optional): Include data analysis (default: true)
  • title (optional): Chart title
  • options (optional): Additional chart configuration

Example:

{
  "data": [
    {"month": "Jan", "sales": 1200, "profit": 300},
    {"month": "Feb", "sales": 1500, "profit": 450},
    {"month": "Mar", "sales": 1800, "profit": 600}
  ],
  "title": "Q1 Sales Performance",
  "outputFormat": "html",
  "includeAnalysis": true
}

Tool 2: analyze_data

Perform comprehensive data analysis without visualization.

Parameters:

  • data (required): JSON data to analyze
  • analysisType (optional): 'statistical', 'trend', 'correlation', or 'summary'

Example:

{
  "data": [
    {"product": "A", "sales": 1200, "cost": 800},
    {"product": "B", "sales": 1500, "cost": 900}
  ],
  "analysisType": "statistical"
}

Tool 3: create_dashboard

Create a comprehensive dashboard with multiple visualizations.

Parameters:

  • datasets (required): Array of dataset configurations
  • outputFormat (optional): 'html' or 'word' (default: 'html')
  • dashboardTitle (optional): Dashboard title

Example:

{
  "datasets": [
    {
      "data": [{"category": "A", "value": 100}],
      "chartType": "pie",
      "title": "Distribution"
    },
    {
      "data": [{"month": "Jan", "sales": 1200}],
      "chartType": "line",
      "title": "Trend"
    }
  ],
  "dashboardTitle": "Sales Dashboard",
  "outputFormat": "html"
}

📊 Data Format Examples

Simple Object Format

{
  "Category A": 100,
  "Category B": 200,
  "Category C": 150
}

Array of Objects Format

[
  {"category": "A", "value": 100, "target": 120},
  {"category": "B", "value": 200, "target": 180},
  {"category": "C", "value": 150, "target": 160}
]

Time Series Format

[
  {"date": "2024-01-01", "sales": 1200, "expenses": 800},
  {"date": "2024-02-01", "sales": 1500, "expenses": 900},
  {"date": "2024-03-01", "sales": 1800, "expenses": 1000}
]

Network Format

[
  {"source": "A", "target": "B", "value": 10},
  {"source": "B", "target": "C", "value": 20},
  {"source": "A", "target": "C", "value": 15}
]

Gantt Chart Format

[
  {"task": "Planning", "start": "2024-01-01", "end": "2024-01-15"},
  {"task": "Development", "start": "2024-01-16", "end": "2024-02-28"},
  {"task": "Testing", "start": "2024-03-01", "end": "2024-03-15"}
]

🏗️ Architecture

watsonx-visualization-mcp/
├── src/
│   ├── mcp-server/          # MCP server implementation
│   ├── visualization-engine/ # Chart generation
│   ├── analysis-engine/      # Data analysis
│   ├── output-generators/    # Format converters
│   └── utils/               # Helper utilities
├── docs/                    # Documentation
├── examples/                # Usage examples
├── tests/                   # Test suites
└── config/                  # Configuration files

🎨 Styling

All visualizations follow IBM Carbon Design System guidelines:

  • IBM Plex Sans font family
  • Carbon color palette
  • Accessible color contrasts
  • Responsive layouts
  • Professional styling

🧪 Testing

Run tests:

npm test

Run with coverage:

npm run test:coverage

📚 Documentation

🤝 Contributing

Contributions are welcome! Please read our contributing guidelines before submitting PRs.

📄 License

MIT License - see LICENSE file for details

🆘 Support

For issues and questions:

  • GitHub Issues: [Create an issue]
  • Documentation: docs/
  • Examples: examples/

🔄 Version History

v1.0.0 (Current)

  • Initial release
  • 40+ chart types supported
  • Intelligent chart selection
  • Comprehensive analysis engine
  • Multiple output formats
  • Watsonx Orchestrate integration

🙏 Acknowledgments


Made with ❤️ for IBM Watsonx Orchestrate

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