P

mcp-vegalite-server

Created Oct 19, 2025 by isaacwasserman

Language:

Python

Stars:

51

Forks:

15

README

Data Visualization MCP Server

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

# 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"
        ]
    }
  }
}
Last updated: Oct 19, 2025

Publisher info

isaacwasserman's avatar

isaacwasserman

Virsec
Philadelphia, PA
9
followers
2
following
88
repos

More MCP servers built with Python

Stable Diffusion WebUI

Stable Diffusion web UI

By AUTOMATIC1111 160.1K
Transformers

🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

By huggingface 155.5K
PyTorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

By pytorch 96.8K