Data Visualization MCP Server
LocalAbout Data Visualization MCP Server
Data Visualization MCP Server is an MCP server that lets an LLM create charts from data using Vega-Lite syntax. It offers two tools for saving data tables and rendering visualizations, suited to analysis workflows where a model produces charts.
Key features
- 01Charts generated from Vega-Lite specifications
- 02Saved data tables reused for later visualization
- 03Text or PNG output selectable at startup
- 04Text output includes full Vega-Lite spec with data
Use cases
- 01Letting an LLM chart aggregated data
- 02Adding chart generation to Claude Desktop
- 03Returning rendered charts as PNG images
MCP support
This is an MCP server that exposes save_data and visualize_data tools to MCP clients. visualize_data returns either text with an artifact field or a base64-encoded PNG as ImageContent.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEData 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 saveddata(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 visualizedvegalite_specification(string): JSON string representing the Vega-Lite specification
- Returns: If the
--output_typeis set totext, returns a success message with an additionalartifactkey containing the complete Vega-Lite specification with data. If the--output_typeis set topng, returns a base64 encoded PNG image of the visualization using the MPCImageContentcontainer.
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"
]
}
}
}
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.
