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Data Visualization MCP Server

Data Visualization MCP Server

by markomitranic
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

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.

Related MCP server: mcp-plots

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_vegalite",
            "--output-type",
            "png" # or "text"
        ]
    }
  }
}

Usage with uv

uv --directory /Users/markomitranic/Sites/mcp/mcp-vegalite-server run mcp_server_vegalite --output-type png

Usage with Docker

docker build -t mcp-server-vegalite .
docker run -i --rm mcp-server-vegalite --output-type png

Available Tools

2 tools
save_dataB

A tool which allows you to save data to a named table for later use in visualizations. When to use this tool:

  • Use this tool when you have data that you want to visualize later. How to use this tool:

  • Provide the name of the table to save the data to (for later reference) and the data itself.

Inputs: name (required), data (required).

visualize_dataA

A tool which allows you to produce a data visualization using the Vega-Lite grammar. When to use this tool:

  • At times, it will be advantageous to provide the user with a visual representation of some data, rather than just a textual representation.

  • This tool is particularly useful when the data is complex or has many dimensions, making it difficult to understand in a tabular format. It is not useful for singular data points. How to use this tool:

  • Prior to visualization, data must be saved to a named table using the save_data tool.

  • After saving the data, use this tool to visualize the data by providing the name of the table with the saved data and a Vega-Lite specification.

Inputs: data_name (required), vegalite_specification (required).

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

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    TDQS

    A3.6/5.0

    Scored across 2 tools

    Disambiguation5/5

    The two tools have completely distinct purposes with no overlap. 'save_data' is for storing data in a table, while 'visualize_data' is for creating visualizations from saved data. The descriptions clearly differentiate their functions and usage contexts.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun naming pattern ('save_data' and 'visualize_data'). The naming style is uniform throughout, using snake_case with clear action-object pairs that accurately reflect their functions.

    Tool Count2/5

    With only 2 tools, this server feels severely under-scoped for a data visualization domain. A complete visualization workflow would typically require tools for data manipulation, chart type selection, configuration adjustments, or exporting visualizations. The current set is too minimal for effective agent use.

    Completeness2/5

    The tool surface has significant gaps for a data visualization server. There are no tools for data transformation, filtering, or aggregation before visualization. Missing are tools for different visualization types, chart customization, or exporting results. The dependency on Vega-Lite specifications without helper tools creates a steep learning curve for agents.

    Maintenance

    ActivityInactive
    ResponsivenessNo recent community issues

    Resources

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