What is the key difference between Csvglow and Charted?

Csvglow belongs to the Data Visualization category with local stdio execution, while Charted belongs to the Data Visualization category with local stdio execution.

How do I install Csvglow or Charted in Claude Desktop or Cursor?

Copy the mcpServers JSON configuration snippet provided on this page into your claude_desktop_config.json or ~/.cursor/mcp.json file and restart your AI client.

Are Csvglow and Charted free or paid?

Csvglow operates under a Free / Open Source model (No auth required). Charted operates under a Free / Open Source model (No auth required).

Which MCP server has more tools and community activity?

Csvglow lists 6 tools with 3 views and 13 GitHub stars. Charted lists 6 tools with 7 views and 11 GitHub stars.

Can I use both Csvglow and Charted together in the same MCP host?

Yes! MCP hosts like Claude Desktop, Cursor, Windsurf, Cline, and VS Code support configuring multiple servers under the mcpServers object simultaneously.

Side-by-Side Model Context Protocol Comparison

Csvglow vs Charted

In-depth architectural comparison of the Csvglow and Charted MCP servers. Compare execution transports, security boundaries, tool capabilities, quality scores, and ready-to-paste client installation snippets for Claude, Cursor, Windsurf, and VS Code.

At a Glance & Executive Verdict

Csvglow

Data Visualization · Local stdio

Quality: 49/100 (Fair) | Auth: No auth required

Charted

Data Visualization · Local stdio

Quality: 52/100 (Good) | Auth: No auth required

Verdict Summary: Choose Csvglow if you need specialized Data Visualization tools running via a local process. Choose Charted if your workspace requires Data Visualization integration with local subprocess execution. Both servers can be configured concurrently in your client's mcpServers manifest.

Which MCP Server Should You Choose?

Choose Csvglow when:

You need dedicated capabilities in the Data Visualization domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: No auth required (Free / Open Source).
Primary tools included: CSV, TSV, XLS, and XLSX input, Automatic column-type detection, Interactive ECharts visualizations.

Explore Csvglow Details

Choose Charted when:

You need dedicated capabilities in the Data Visualization domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: No auth required (Free / Open Source).
Primary tools included: Supports 15 chart types, Accepts JSON and CSV data, Exports SVG, PNG, HTML, and data URLs.

Explore Charted Details

Feature & Specification Comparison

Specification	Csvglow Ratnaditya-J Data Visualization	Charted marzukia Data Visualization
Summary
Category & Scope	Data Visualization	Data Visualization
Quality signal

Tools & Capabilities Breakdown

Csvglow Tools (6)

CSV, TSV, XLS, and XLSX input

Automatic column-type detection

Interactive ECharts visualizations

Correlation and cross-column analysis

Sortable and filterable data table

Offline self-contained HTML output

Charted Tools (6)

Supports 15 chart types

Ready-to-Paste Client Configurations

Paste either (or both) of these JSON server blocks into your client config file (e.g. claude_desktop_config.json or ~/.cursor/mcp.json).

Csvglow Configuration

mcpServers (Claude Desktop / Cursor)

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

Charted Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "marzukia-charted": {
      "command": "uvx",
      "args": [
        "--from",
        "charted[mcp]",
        "charted-mcp"
      ]
    }
  }
}

Frequently Asked Questions

Csvglow is categorized under Data Visualization and uses a local stdio subprocess. In contrast, Charted belongs to Data Visualization using local stdio subprocess. Select Csvglow when you need capabilities focused on data visualization and Charted when you require tools for data visualization.

More alternatives to Csvglow More alternatives to Charted Data Visualization category hub Canonical compare URL