Data Visualization MCP Server

Data Visualization MCP Server

MCP server for data visualization using Vega-Lite.

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Data Visualization MCP Server enables large language models to visualize data through a standardized interface using Vega-Lite specifications. The server provides tools for saving data tables and generating visualizations as text or PNG images. Integration with platforms like Claude Desktop allows seamless addition of data visualization capabilities to LLM workflows.

Key Features

Saves tabular data for future visualization
Generates Vega-Lite visualizations from saved data
Returns visualization as Vega-Lite JSON specification or PNG image
Compatible with Claude Desktop
Supports output type selection (text or png)
Provides Model Context Protocol-compliant interface
Accepts data tables as arrays of objects
Customizable command-line deployment
Secure artifact output handling
Integrates with LLM workflows

Use Cases

Enabling LLMs to create interactive data visualizations
Saving and retrieving data for repeated analysis
Serving as a backend for visualization-heavy AI applications
Integrating advanced chart rendering into AI assistants
Generating presentation-ready images from tabular data
Automating data exploration within language model interfaces
Powering dashboards with LLM-controlled charts
Providing visual context in conversational AI tools
Supporting data storytelling with automated visuals
Enabling collaborative exploration of data insights

README

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Data Visualization MCP Server

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Overview

A Model Context Protocol (MCP) server implementation that provides the LLM an interface for visualizing data using Vega-Lite syntax.

Components

Tools

The server offers two core tools:

  • save_data
    • Save a table of data agregations to the server for later visualization
    • Input:
      • name (string): Name of the data table to be saved
      • data (array): Array of objects representing the data table
    • Returns: success message
  • visualize_data
    • Visualize a table of data using Vega-Lite syntax
    • Input:
      • data_name (string): Name of the data table to be visualized
      • vegalite_specification (string): JSON string representing the Vega-Lite specification
    • Returns: If the --output_type is set to text, returns a success message with an additional artifact key containing the complete Vega-Lite specification with data. If the --output_type is set to png, returns a base64 encoded PNG image of the visualization using the MPC ImageContent container.

Usage with Claude Desktop

python
# Add the server to your claude_desktop_config.json
{
  "mcpServers": {
    "datavis": {
        "command": "uv",
        "args": [
            "--directory",
            "/absolute/path/to/mcp-datavis-server",
            "run",
            "mcp_server_datavis",
            "--output_type",
            "png" # or "text"
        ]
    }
  }
}

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Repository Details

Language Python
Default Branch main
Size 24 KB
Contributors 3
MCP Verified Nov 12, 2025

Programming Languages

Python
85.97%
Dockerfile
14.03%

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