Csvglow MCP Server

@Ratnaditya-J

代码仓库

基本信息

分类

其他

传输方式

stdio

作者

Ratnaditya-J

提交者

Ratnaditya-J

关于 Csvglow MCP Server

暂无概览

Csvglow MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

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

Csvglow MCP Server 工具

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点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。

概览

What is Csvglow?

Csvglow generates beautiful, interactive HTML dashboards from CSV or Excel files with a single command and zero configuration. It produces a self-contained HTML file that opens in the browser, featuring auto-detected charts, multi-column narrative insights, correlations, and a sortable data table. It also functions as an MCP (Model Context Protocol) tool for AI-compatible clients and as an OpenClaw skill.

How to use Csvglow?

Install via pip install csvglow or run directly with npx (npx csvglow data.csv). Use csvglow data.csv to generate a dashboard and open it in the browser. Additional options include -o for a custom output path and --no-open to prevent auto-opening. For MCP server mode, add a configuration entry to your client’s MCP config file (e.g., .cursor/mcp.json) with "command": "npx" and "args": ["-y", "csvglow", "--mcp"] (or "command": "csvglow" if installed via pip).

Key features of Csvglow

Smart multi-column narrative analysis with contradiction detection
Histograms for numeric columns with stats sidebar
Bar charts for categorical columns
Automatic categorical × numeric cross analysis with mean lines
Time series line charts with area fill for date columns
Correlation heatmap and scatter plots for highly correlated pairs

Use cases of Csvglow

Instantly visualize any CSV or Excel file as a rich dashboard
Use as an MCP tool so an AI assistant can generate dashboards from file paths
Embed a self-contained, offline HTML report with charts and data table
Quickly share interactive dashboards with stakeholders (no server needed)
Analyze large datasets (100k+ rows) with smart sampling

常见问题

What file formats does Csvglow support?

It supports `.csv`, `.tsv` (auto-detected delimiter), `.xls`, and `.xlsx` (first sheet only; multi-sheet support is planned).

Can Csvglow handle large files?

Yes, for files with 100k+ rows it uses smart sampling to keep the output performant.

How do I use Csvglow as an MCP server?

Add a JSON entry to your MCP-compatible client’s config file (e.g., `.cursor/mcp.json`) with the command `npx -y csvglow --mcp` or `csvglow --mcp` if installed via pip. No extra installation is needed when using npx.

Does the output require an internet connection?

No, the output is a single self-contained HTML file that works offline with no server or CDN dependencies.

Is there any installation required for the MCP mode?

When using npx, no installation is needed. If you prefer to install first, run `pip install csvglow` and use `csvglow --mcp`.

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