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ceeyang-ai

Viz MCP Server

by ceeyang-ai
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Python
Remote

Viz MCP Server 📊

Python License Stars MCP GitHub

A Model Context Protocol (MCP) server for data visualization — generate bar charts, line charts, pie charts, scatter plots, and histograms. Returns SVG (inline) or PNG (file).

Built for AI agents. Works with Hermes Agent, Claude Code, Cursor, and any MCP-compatible client.

✨ Features

Tool

Description

create_bar_chart

Bar chart (vertical/horizontal) with value labels

create_line_chart

Line chart with area fill, markers, trend

create_pie_chart

Pie/donut chart with percentage labels

create_scatter_plot

Scatter plot with optional regression line

create_histogram

Histogram with mean line, optional cumulative

All tools support:

  • 4 color palettes: default, vibrant, pastel, monochrome

  • SVG output (inline for MCP response) or PNG output (saved to file)

  • Custom titles, axis labels

  • Clean matplotlib styling (no chartjunk)

Related MCP server: Quick Chart MCP Server

🚀 Quick Start

# Install from GitHub
pip install git+https://github.com/ceeyang-ai/viz-mcp-server.git

# Run as MCP server
viz-mcp-server

🔌 Usage with Hermes Agent

Add to ~/.hermes/config.yaml:

mcp_servers:
  viz:
    command: "viz-mcp-server"

Restart Hermes → tools available as mcp_viz_create_bar_chart, etc.

📖 Examples

Bar Chart

# Via MCP tool call
result = create_bar_chart(
    values=[10, 25, 15, 30, 20],
    labels=["Q1", "Q2", "Q3", "Q4", "Q5"],
    title="Quarterly Revenue",
    ylabel="Revenue ($K)",
    palette="vibrant"
)

Scatter with Trend Line

result = create_scatter_plot(
    x_values=[1, 2, 3, 4, 5, 6, 7, 8],
    y_values=[2, 3, 5, 7, 11, 13, 17, 19],
    title="Growth Analysis",
    regression_line=True
)

Histogram

result = create_histogram(
    values=[12, 15, 13, 20, 19, 18, 14, 16, 22, 25, 21, 17],
    bins=8,
    title="Score Distribution",
    xlabel="Score"
)

🛠 Requirements

  • Python 3.10+

  • matplotlib ≥ 3.7

  • numpy ≥ 1.24

  • mcp ≥ 1.0

👨‍💻 Development

git clone https://github.com/ceeyang-ai/viz-mcp-server.git
cd viz-mcp-server
pip install -e .
viz-mcp-server  # Start MCP server

📄 License

MIT

Install Server
A
license - permissive license
A
quality
B
maintenance

How are these scores calculated?

Maintenance

–Maintainers
–Response time
–Release cycle
1Releases (12mo)
Commit activity

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