Data Visualization MCP Server

Name: Data Visualization MCP Server
Author: isaacwasserman

@isaacwasserman

リポジトリ

Data Visualization MCP Server について

概要はまだありません

基本情報

カテゴリ

データと分析

ランタイム

python

トランスポート

stdio

公開者

isaacwasserman

設定

標準の設定はありません

このサーバーの README には解析可能な MCP 設定ブロックが含まれていません。インストール手順はリポジトリをご確認ください。

リポジトリ

ツール

Save a table of data agregations to the server for later visualization

Visualize a table of data using Vega-Lite syntax

概要

What is Data Visualization MCP Server?

A Model Context Protocol (MCP) server that gives large language models an interface to visualize data using Vega‑Lite syntax. It is designed for use with MCP clients such as Claude Desktop to generate charts and graphs from structured data.

How to use Data Visualization MCP Server?

Add the server to your Claude Desktop configuration (claude_desktop_config.json) by specifying the command uv, the directory path, the Python module mcp_server_datavis, and the --output_type flag (set to either png or text). Use the save_data tool to store a data table and the visualize_data tool to render that data as a Vega‑Lite visualization.

Key features of Data Visualization MCP Server

Two core tools: save_data and visualize_data
Supports Vega‑Lite specification for chart generation
Output can be text (Vega‑Lite spec) or PNG image
Data tables are saved on the server for reuse
Integrates with MCP clients like Claude Desktop

Use cases of Data Visualization MCP Server

Generate a PNG chart from aggregated data returned by an LLM
Iteratively refine a Vega‑Lite specification before rendering
Create reusable data tables for multiple visualizations in a session
Embed a Vega‑Lite specification in a text response for rendering elsewhere

FAQ from Data Visualization MCP Server

What runtime dependencies does it require?

It requires Python and uv package manager. The mcp_server_datavis module is invoked via uv run.

How are data tables persisted?

Data tables are saved in the server’s memory using the save_data tool and are referenced by name in visualize_data. No external database is used.

What output formats are supported?

Two output types are supported: text (returns a JSON Vega‑Lite specification) and png (returns a base64‑encoded PNG image wrapped in an MCP ImageContent container).

Is authentication required?

No authentication or authorization mechanism is described in the README. The server runs locally via stdio transport.

What transport protocol does it use?

It uses standard MCP stdio transport, invoked from the command line.

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