Data Visualization MCP Server
@isaacwasserman
About Data Visualization MCP Server
No overview available yet
Basic information
Config
No standard config provided
This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.
RepositoryTools
2Save a table of data agregations to the server for later visualization
Visualize a table of data using Vega-Lite syntax
Overview
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_dataandvisualize_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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