Csvglow README

The full upstream README, mirrored for reference. Install config, tool schemas, adoption signals and our own overview live on the Csvglow listing page.

csvglow

csvglow MCP server

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

bash
csvglow sales.csv

Opens a self-contained HTML dashboard in your browser with auto-detected charts, smart multi-column insights, correlations, and a sortable data table. Dark gradient theme. Copy any chart to your clipboard.

Install

Terminal
pip install csvglow

Or via npx (no install needed):

Terminal
npx csvglow data.csv

Usage

bash
csvglow data.csv                    # CSV to 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 findings — multi-column narrative analysis that cross-references metrics to surface contradictions, efficiency gaps, and top/underperformers
  • Histograms for every numeric column with mean, median, std, quartiles, and outlier counts
  • Bar charts for categorical columns
  • Cross analysis — automatic categorical x numeric crosstabs with overall mean lines
  • Time series line charts with area fill for date columns
  • Correlation heatmap between numeric columns
  • Scatter plots for highly correlated pairs (|r| > 0.7)
  • Sortable, filterable data table (first 1000 rows)
  • Copy button on each chart 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 any MCP-compatible client. Once configured, ask your AI assistant to generate a dashboard from a file path.

Pick your client and add csvglow to its MCP config file:

ClientConfig file location
Cursor.cursor/mcp.json in your project root
Windsurf~/.windsurf/mcp.json

Add this to the config:

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

Uses npx so there's nothing extra to install.

If you already have csvglow installed via pip, use "command": "csvglow" with "args": ["--mcp"] instead.

OpenClaw Skill

csvglow is available as an OpenClaw skill. Any OpenClaw-compatible client can discover and use it automatically — no manual config needed.

Supported formats

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

Changelog

0.1.0

  • Initial release
  • Auto-detection of column types (numeric, categorical, datetime, identifier)
  • Smart findings: contradiction detection, efficiency analysis, top/underperformer identification across multiple columns
  • Histograms with stats sidebar, bar charts, cross-analysis crosstabs, time series, correlation heatmap, scatter plots
  • Sortable/filterable data table
  • Copy-to-clipboard for all charts
  • MCP server mode (csvglow --mcp)
  • OpenClaw skill support
  • Smart sampling for large files (100k+ rows)

Roadmap

  • Multi-sheet Excel support
  • Multi-file support with join keys
  • Light theme
  • Custom color palettes
  • PDF export

License

MIT