Stats Compass

io.github.oogunbiyi21由 GitHub 账号 oogunbiyi21 发布v0.3.37更新于 Oct 29, 2026

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

发布方自己的服务:Garmin & Strava for Claude and ChatGPT

已验证Streamable HTTP可网页运行数据与分析AI 与机器学习

概览

AI 生成的概览

Stats Compass 为助手提供 50 多个基于 pandas 的工具,用于加载、清洗、探索、可视化数据并训练模型,还包含销售分析流程。

可以做什么
  • 加载数据:读取 CSV/Excel、示例数据集,列出已加载的 DataFrame,在文件夹中查找数据文件
  • 清洗与转换:删除空值、填补缺失、去重、处理异常值,以及筛选、分组、透视、逆透视、编码、新增列
  • 探索与检验:描述统计、相关性、假设检验、数据质量检查
  • 可视化:直方图、散点图、柱状图、ROC 曲线、混淆矩阵
  • 建模:分类、回归与时间序列预测
  • 销售分析:判断每周销量是否异常、季节性规律、促销带来的增量及促销后的回落
适用场景
适合让助手直接完成表格数据分析而无需自己写 Python:对 CSV 或 Excel 做快速探索性分析、清洗、绘图、统计检验、简单机器学习模型,或零售销量与促销效果分析。
运行要求
可使用托管的远程端点(需 OAuth 登录),或在本地通过 pip/uvx 安装 stats-compass-mcp 包(需要 Python)。本地模式按路径读取文件,远程模式通过浏览器上传。自建服务时可能需要 STATS_COMPASS_AUTH_TOKEN 和 STATS_COMPASS_SECRET_KEY。
安装前请注意
本地模式会读取助手被指定的文件路径,请只指向愿意暴露的目录。自建并对外公开时需设置 bearer 令牌和密钥;未设置时服务器会拒绝公开地址,而 --no-auth 会关闭该保护。上传文件、导出结果和会话数据会保留到空闲会话被清理,下载链接 24 小时后过期。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Stats Compass,将其添加到工作区。
  2. 连接 所需的 凭据。它们会被私密存储,绝不会在公开页面上展示。
  3. 为需要使用其工具的对话启用该服务。

Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。

交给智能体安装

把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体,或 SourceWeft 对话中。智能体会读取该服务器的安装指南,先向你展示发布者、端点和登录方式,经你同意后再把它添加到你的客户端。密钥不会写进任何命令。

阅读 https://sourceweft.com/mcp/io.github.oogunbiyi21%2Fstats-compass/install.md,并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前,先告诉我它的发布者、端点和登录方式,等我确认。不要把 API 密钥写进命令或我会提交的文件;问我密钥应从哪里获取。

查看智能体所依据的安装指南

其他 MCP 客户端

把它添加到你客户端的 mcpServers 配置中。 客户端会在首次连接时完成 OAuth 登录。

{
  "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

来源:README.md,提交 e1ce90c

工具

0
该服务器需要登录,因此 SourceWeft 无法在没有账号的情况下读取其工具,也未收录。已连接账号所能看到的内容可能因账号及其权限而异。

版本历史

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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