What is the key difference between MCP Gnu Units and Data Profiler MCP?

MCP Gnu Units belongs to the Data Science Tools category with local stdio execution, while Data Profiler MCP belongs to the Data Science Tools category with local stdio execution.

How do I install MCP Gnu Units or Data Profiler MCP 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 MCP Gnu Units and Data Profiler MCP free or paid?

MCP Gnu Units operates under a Free / Open Source model (No auth required). Data Profiler MCP operates under a Free / Open Source model (No auth required).

Which MCP server has more tools and community activity?

MCP Gnu Units lists 5 tools with 4 views and 1 GitHub stars. Data Profiler MCP lists 7 tools with 4 views and 2 GitHub stars.

Can I use both MCP Gnu Units and Data Profiler MCP 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

MCP Gnu Units vs Data Profiler MCP

In-depth architectural comparison of the MCP Gnu Units and Data Profiler MCP 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

MCP Gnu Units

Data Science Tools · Local stdio

Quality: 51/100 (Good) | Auth: No auth required

Data Profiler MCP

Data Science Tools · Local stdio

Quality: 59/100 (Good) | Auth: No auth required

Verdict Summary: Choose MCP Gnu Units if you need specialized Data Science Tools tools running via a local process. Choose Data Profiler MCP if your workspace requires Data Science Tools integration with local subprocess execution. Both servers can be configured concurrently in your client's mcpServers manifest.

Which MCP Server Should You Choose?

Choose MCP Gnu Units when:

You need dedicated capabilities in the Data Science Tools domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: No auth required (Free / Open Source).
Primary tools included: Converts more than 3,000 units, Evaluates compound unit expressions, Reduces quantities to SI base units.

Explore MCP Gnu Units Details

Choose Data Profiler MCP when:

You need dedicated capabilities in the Data Science Tools domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: No auth required (Free / Open Source).
Primary tools included: profile_dataset, preview_data, column_stats.

Explore Data Profiler MCP Details

Feature & Specification Comparison

Specification	MCP Gnu Units laszlopere Data Science Tools	Data Profiler MCP haiiibin Data Science Tools
Summary	Unit conversion and dimensional analysis backed by the bundled GNU units database (3000+ units, compound expressions, reduction to SI base units). Offline and deterministic. uvx mcp-gnu-units.	Profiles tabular data files (CSV, TSV, Parquet, Excel, JSON) for LLM agents: one-call dataset overview, per-column statistics, a data-quality audit (missing values, duplicates, mixed types, outliers), and memory-saving dtype suggestions. Pure Python (pandas); files are read locally and nothing leaves your machine. pip install data-profiler-mcp.
Category & Scope

Tools & Capabilities Breakdown

MCP Gnu Units Tools (5)

Converts more than 3,000 units

Evaluates compound unit expressions

Reduces quantities to SI base units

Searches and defines units, prefixes, and constants

Runs offline with deterministic results

Data Profiler MCP Tools (7)

profile_dataset

Profile a tabular data file in one call: the fastest way to understand a dataset. Reads the file at ``path`` (CSV, TSV, Parquet, Excel or JSON/JSONL, detected from the extension) and returns a structured overview: - file metadata (format, size), - shape (row and column counts, and whether the profile was sampled), - total memory footprint, - a missing-value summary and a duplicate-row count, - a per-column summary (dtype, inferred type, null %, unique %, sample values, and basic stats for numeric/datetime columns), and - a list of plain-language data-quality flags. Use this first whenever a user points you at a data file and wants to know what is in it. ``max_rows`` caps how many rows are read (default: up to one million); the result flags when the file was larger and the stats are a head sample. Pass 0 to remove the cap entirely.

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).

MCP Gnu Units Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "laszlopere-mcp-gnu-units": {
      "command": "uvx",
      "args": [
        "mcp-gnu-units"
      ]
    }
  }
}

Data Profiler MCP Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "haiiibin-data-profiler-mcp": {
      "command": "uvx",
      "args": [
        "data-profiler-mcp"
      ]
    }
  }
}

Frequently Asked Questions

MCP Gnu Units is categorized under Data Science Tools and uses a local stdio subprocess. In contrast, Data Profiler MCP belongs to Data Science Tools using local stdio subprocess. Select MCP Gnu Units when you need capabilities focused on data science tools and Data Profiler MCP when you require tools for data science tools.

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