Stats Compass

io.github.oogunbiyi21由 GitHub 帳號 oogunbiyi21 發布v0.3.37更新於 Oct 29, 2026

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

發布方自己的服務:Garmin & Strava for Claude and ChatGPT

已驗證Streamable HTTP可網頁執行資料與分析AI 與機器學習

概覽

AI 產生的概覽

Stats Compass 為助理提供 50 多個以 pandas 為基礎的工具,可載入、清理、探索、視覺化資料並訓練模型,另含銷售分析流程。

可以做什麼
  • 載入資料:讀取 CSV/Excel、範例資料集,列出已載入的 DataFrame,在資料夾中尋找資料檔
  • 清理與轉換:刪除空值、補值、去除重複、處理離群值,以及篩選、分組、樞紐、反樞紐、編碼、新增欄位
  • 探索與檢定:描述統計、相關性、假設檢定、資料品質檢查
  • 視覺化:直方圖、散佈圖、長條圖、ROC 曲線、混淆矩陣
  • 建模:分類、迴歸與時間序列預測
  • 銷售分析:判斷每週銷量是否異常、季節性規律、促銷帶來的增量與促銷後的回落
適用情境
適合讓助理直接完成表格式資料分析而不必自行撰寫 Python:對 CSV 或 Excel 做快速探索分析、清理、繪圖、統計檢定、簡單機器學習模型,或零售銷量與促銷成效分析。
執行需求
可使用託管的遠端端點(需 OAuth 登入),或在本地以 pip/uvx 安裝 stats-compass-mcp 套件(需要 Python)。本地模式依路徑讀取檔案,遠端模式透過瀏覽器上傳。自行架設服務時可能需要 STATS_COMPASS_AUTH_TOKEN 與 STATS_COMPASS_SECRET_KEY。
安裝前請注意
本地模式會讀取助理被指定的檔案路徑,請只指向願意曝露的資料夾。自行架設並對外公開時需設定 bearer 權杖與金鑰;未設定時伺服器會拒絕公開位址,而 --no-auth 會關閉該保護。上傳檔案、匯出結果與工作階段資料會保留到閒置工作階段被清除,下載連結 24 小時後過期。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Stats Compass,將其新增到工作區。
  2. 連接 所需的 憑證。它們會被私密儲存,絕不會在公開頁面上展示。
  3. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/io.github.oogunbiyi21%2Fstats-compass/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。 客戶端會在首次連接時完成 OAuth 登入。

{
  "mcpServers": {
    "stats-compass": {
      "type": "http",
      "url": "https://mcp.statscompass.io/mcp"
    }
  }
}

README

[Stats Compass Logo]

stats-compass-mcp

Turn your LLM into a data analyst. Multiple data science tools via MCP.

[PyPI version] [Python 3.11+] [License: MIT]

[Demo: Loading and exploring data]

Quick Start

bash
pip install stats-compass-mcp

Claude Desktop

bash
stats-compass-mcp install --client claude

VS Code (GitHub Copilot)

bash
stats-compass-mcp install --client vscode

Claude Code (CLI)

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

Note: The first connection may fail while uvx downloads the package. If this happens, disable and re-enable Stats Compass in your MCP settings — subsequent connections will be instant.

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, melt, encode, add columns
EDADescribe, correlations, hypothesis tests, data quality
VisualizationHistograms, scatter, bar, ROC curves, confusion matrix
ML WorkflowsClassification, regression, time series forecasting
SalesIs this week expected, a real change or noise? What does each month usually bring? What did a promotion add, and did sales dip after it? Daily or weekly sales, per retailer or product, with a promotion calendar

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

How to Prompt

Start your message with "Use stats compass to..." — this tells the AI to use the Stats Compass tools instead of trying to write code or use other methods.

Use stats compass to load ~/Downloads/sales.csv and run EDA on itUse stats compass to find my CSV files in DownloadsUse stats compass to clean the dataset and handle missing valuesUse stats compass to create a histogram of the price columnUse stats compass to test if there's a significant difference in scores between group A and BUse stats compass to train a classification model to predict churnUse stats compass to load sell_out.xlsx and tell me if last week's sales at each retailer were unusual, leaving out the promotions in promo_calendar.csvUse stats compass to measure what the June promotion added at Tesco, using promo_calendar.csv

Tip: Without this prefix, some AI clients may try to write Python code or use shell commands instead of the Stats Compass tools — especially for tasks like finding files on your machine.

Loading Files

Local mode: Start with "Use stats compass to load..." and provide the file path or folder.

Use stats compass to load the CSV at ~/Downloads/sales.csvUse stats compass to find my data files in ~/Documents

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

Remote Server Mode

For Docker deployments or multi-client setups:

bash
stats-compass-mcp serve --port 8000

serve binds 127.0.0.1 by default. To accept connections from other machines, set a bearer token of at least 16 characters and bind a public address:

bash
export STATS_COMPASS_AUTH_TOKEN="$(openssl rand -hex 24)"export STATS_COMPASS_SECRET_KEY="$(openssl rand -hex 32)"   # encrypts upload/download linksstats-compass-mcp serve --host 0.0.0.0 --port 8000

Clients send Authorization: Bearer <token>. Without a token the server refuses a public address; --no-auth overrides that, with a warning, for a network you trust. Each session reads only its own uploads and writes only its own exports. Upload and download links carry an encrypted token that expires (downloads after 24 hours, STATS_COMPASS_DOWNLOAD_TTL_SECONDS), never the session id.

A session idle for 24 hours is removed, with its data, models and exported files (STATS_COMPASS_SESSION_IDLE_HOURS; 0 turns it off). A session in the middle of a tool call is never removed. A server that embeds the tools runs its own sweep with SessionManager.evict_idle(max_idle).

File Uploads

When running remotely, users can upload files via browser:

[File Upload Interface]
You: I want to upload a fileAI: Open this link to upload: http://localhost:8000/upload?session_id=abc123
[Upload in browser]
You: I uploaded sales.csvAI: ✅ Loaded sales.csv (1,000 rows × 8 columns)

Downloading Results

Export DataFrames, plots, and trained models:

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

Connect Clients to Remote Server

VS Code (native HTTP support):

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

Claude Desktop (via mcp-proxy):

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

Docker

bash
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✅ Supported
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

來源:README.md,提交 e1ce90c

工具

0
該伺服器需要登入,因此 SourceWeft 無法在沒有帳號的情況下讀取其工具,也未收錄。已連接帳號所能看到的內容可能因帳號及其權限而異。

版本歷史

5
  1. v0.3.37最新Oct 29, 2026
  2. v0.3.35Oct 23, 2026
  3. v0.3.34Oct 12, 2026
  4. v0.3.33Oct 10, 2026
  5. v0.3.28Sep 16, 2026

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其他 Stats 整合