MCP Hub
Back to servers

Stats Compass

50+ pandas-powered tools for data loading, cleaning, visualization, and ML workflows

Stars
1
Updated
Jan 27, 2026

Quick Install

uvx stats-compass-mcp
Stats Compass Logo

stats-compass-mcp

Turn your LLM into a data analyst. 50+ pandas tools via MCP.

PyPI version Python 3.11+ License: MIT

Demo: Loading and exploring data

Quick Start

pip install stats-compass-mcp

Claude Desktop

stats-compass-mcp install --client claude

VS Code (GitHub Copilot)

stats-compass-mcp install --client vscode

Claude Code (CLI)

claude mcp add stats-compass -- uvx stats-compass-mcp run

Restart your client and start asking questions about your data.

What Can It Do?

Demo: Cleaning and transforming data
CategoryExamples
Data LoadingLoad CSV/Excel, sample datasets, list DataFrames
CleaningDrop nulls, impute, dedupe, handle outliers
TransformsFilter, groupby, pivot, encode, add columns
EDADescribe, correlations, hypothesis tests, data quality
VisualizationHistograms, scatter, bar, ROC curves, confusion matrix
ML WorkflowsClassification, regression, time series forecasting

Run stats-compass-mcp list-tools to see all available tools.

Loading Files

Local mode: Provide the absolute file path.

You: Load the CSV at /Users/me/Downloads/sales.csv

Remote/HTTP mode: Use the upload feature (see below).

Remote Server Mode

For Docker deployments or multi-client setups:

stats-compass-mcp serve --port 8000

File Uploads

When running remotely, users can upload files via browser:

File Upload Interface
You: I want to upload a file
AI: Open this link to upload: http://localhost:8000/upload?session_id=abc123

[Upload in browser]

You: I uploaded sales.csv
AI: ✅ Loaded sales.csv (1,000 rows × 8 columns)

Downloading Results

Export DataFrames, plots, and trained models:

You: Save the cleaned data as a CSV
AI: ✅ Saved. Download: http://localhost:8000/exports/.../cleaned_data.csv

Connect Clients to Remote Server

VS Code (native HTTP support):

{
  "servers": {
    "stats-compass": { "url": "http://localhost:8000/mcp" }
  }
}

Claude Desktop (via mcp-proxy):

{
  "mcpServers": {
    "stats-compass": {
      "command": "uvx",
      "args": ["mcp-proxy", "--transport", "streamablehttp", "http://localhost:8000/mcp"]
    }
  }
}

Docker

docker run -p 8000:8000 -e STATS_COMPASS_SERVER_URL=https://your-domain.com stats-compass-mcp

Client Compatibility

ClientStatus
Claude Desktop✅ Recommended
VS Code Copilot✅ Supported
Claude Code CLI✅ Supported
Cursor⚠️ Experimental
GPT / Gemini⚠️ Partial

Configuration

VariableDefaultDescription
STATS_COMPASS_PORT8000Server port
STATS_COMPASS_SERVER_URLhttp://localhost:8000Base URL for upload/download links
STATS_COMPASS_MAX_UPLOAD_MB50Max upload size

Development

See CONTRIBUTING.md for development setup.

🙏 Credits

Landing page template by ArtleSa (u/ArtleSa)

License

MIT

Reviews

No reviews yet

Sign in to write a review