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csvglow

Generate beautiful, interactive HTML dashboards from CSV/Excel files. One command, zero config.

csvglow sales.csv

Opens a self-contained HTML dashboard in your browser with auto-detected charts, correlations, statistics, and a sortable data table. Dark gradient theme. Copy any chart to your clipboard for slide decks.

Install

pip install csvglow

Or via npx (no install needed):

npx csvglow data.csv

Usage

csvglow data.csv                    # CSV → dashboard, opens in browser
csvglow report.xlsx                 # Excel works too
csvglow data.csv -o dashboard.html  # Custom output path
csvglow data.csv --no-open          # Don't auto-open browser

What it generates

  • Smart insights — multi-column narrative analysis (e.g. "Gadget Y has the highest discount yet lowest revenue — consider discontinuing")
  • Summary stats — row count, column count, data types, missing values
  • Histograms — for every numeric column, with mean/median/std/quartiles sidebar
  • Bar charts — top values for categorical columns
  • Cross analysis — automatic categorical × numeric crosstabs with overall mean lines
  • Time series — line charts with area fill for date columns
  • Correlation heatmap — auto-detected correlations between numeric columns
  • Scatter plots — auto-generated for highly correlated pairs (|r| > 0.7)
  • Outlier detection — IQR-based, highlighted per column
  • Data table — sortable, filterable preview (first 1000 rows)
  • Copy button — each chart has a one-click copy for pasting into slides

Output is a single self-contained HTML file. No server, no CDN, works offline.

MCP Server

csvglow works as an MCP tool in Claude Desktop, Cursor, Claude Code, Windsurf, or any MCP-compatible client.

Quick setup (pick one)

Option A — npx (easiest, no Python setup needed):

{
  "mcpServers": {
    "csvglow": {
      "command": "npx",
      "args": ["-y", "csvglow", "--mcp"]
    }
  }
}

Option B — pip install:

pip install csvglow
{
  "mcpServers": {
    "csvglow": {
      "command": "csvglow",
      "args": ["--mcp"]
    }
  }
}

Option C — Claude Code CLI:

claude mcp add csvglow -- csvglow --mcp

Where to put the config

Client Config file
Claude Desktop ~/Library/Application Support/Claude/claude_desktop_config.json (macOS)
Cursor .cursor/mcp.json in your project or ~/.cursor/mcp.json globally
Claude Code ~/.claude/settings.json or run claude mcp add
Windsurf ~/.windsurf/mcp.json

What the MCP tool does

Exposes a single generate_dashboard tool that takes a file path and returns a full HTML dashboard. Your AI assistant can call it like:

"Generate a dashboard from /path/to/sales.csv"

Supported formats

  • .csv / .tsv (auto-detected delimiter)
  • .xls
  • .xlsx (first sheet only — multi-sheet support coming soon)

Roadmap

  • Multi-sheet Excel support — analyze all sheets in a workbook, with per-tab sections or auto-merge when columns match
  • Multi-file support — csvglow sales.csv marketing.csv --join date to correlate data across multiple files with auto-detected or explicit join keys
  • Light theme
  • Custom color palettes
  • PDF export

License

MIT

Metadata

Release files for csvglow 0.1.0

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