MCP ASCII Charts

MCP ASCII Charts tool

typescript

7

GitHub Stars

typescript

Language

6 months ago

First Indexed

2 months ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs

{
  "mcpServers": {
    "gianlucamazza-mcp-ascii-charts": {
      "command": "mcp-ascii-charts",
      "args": []
    }
  }
}

You can run a Model Context Protocol server that renders pure ASCII charts directly in your terminal, enabling lightweight, no-GUI visualizations that work well on servers or via SSH while integrating with MCP clients.

How to use

Install and run the ASCII charts MCP server locally, then connect your MCP client to visualize data as line, bar, scatter, histogram, or sparkline charts. Start the server in a terminal and use your MCP client’s usual workflow to send data series and labels to the server for on-the-fly rendering.

How to install

Prerequisites: you need Node.js and npm installed on your system.

# Install globally from npm (required for MCP servers)
npm install -g mcp-ascii-charts

# Or install from GitHub
npm install -g git+https://github.com/gianlucamazza/mcp-ascii-charts.git

Once installed, start the server using the MCP command shown in the example configuration.

mcp-ascii-charts

Configuration and usage notes

This server runs as a local MCP process. It exposes an endpoint via standard input/output for your MCP client to connect and send chart data. You can request different chart types and adjust dimensions and styles as your terminal and workflow permit.

Tools and capabilities

The server supports multiple chart types suitable for terminal dashboards, including line charts, bar charts, scatter plots, histograms, and sparklines. You can create charts from numeric data arrays with optional labels and titles.

Usage examples

After starting the server, send data series from your MCP client to render visuals in your terminal. Use line charts for temporal trends, bar charts for category comparisons, and sparklines for compact summaries in dashboards.

Available tools

create_line_chart

Generate line charts for temporal data

create_bar_chart

Create horizontal/vertical bar charts

create_scatter_plot

Visualize correlations between variables

create_histogram

Show frequency distributions

create_sparkline

Mini-charts for compact dashboards