stats-compass

@oogunbiyi21/stats-compass

Hosted

0 Stars 15 次浏览 oogunbiyi21 更新于 2026-08-23

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

开发者工具

MCP 服务配置

复制以下 JSON 到 OPClaw 或其他 MCP 客户端的配置文件中即可使用

{
  "mcpServers": {
    "stats-compass-mcp": {
      "args": [
        "stats-compass-mcp@0.2.9"
      ],
      "command": "uvx"
    }
  }
}

可用工具（5 个）

该服务在 MCP 协议中暴露的工具，AI 可按需调用

tavily_search 14 个参数需填 1 项 Search the web for current information on any topic. Use for news, facts, or data beyond your knowledge cutoff. Returns snippets and source URLs.

Search the web for current information on any topic. Use for news, facts, or data beyond your knowledge cutoff. Returns snippets and source URLs.

必填参数：query

tavily_extract 6 个参数需填 1 项 Extract content from URLs. Returns raw page content in markdown or text format.

Extract content from URLs. Returns raw page content in markdown or text format.

必填参数：urls

tavily_crawl 11 个参数需填 1 项 Crawl a website starting from a URL. Extracts content from pages with configurable depth and breadth.

Crawl a website starting from a URL. Extracts content from pages with configurable depth and breadth.

必填参数：url

tavily_map 8 个参数需填 1 项 Map a website's structure. Returns a list of URLs found starting from the base URL.

Map a website's structure. Returns a list of URLs found starting from the base URL.

必填参数：url

tavily_research 2 个参数需填 1 项 Perform comprehensive research on a given topic or question. Use this tool when you need to gather information from multiple sources to answer a question or complete a task. Returns a detailed response based on the research findings.

Perform comprehensive research on a given topic or question. Use this tool when you need to gather information from multiple sources to answer a question or complete a task. Returns a detailed response based on the research findings.

必填参数：input

服务介绍

<!- - mcp-name: io.github.oogunbiyi21/stats-compass - ->

stats-compass-mcp

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

# 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?

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:

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

# Configuration

# Development

See CONTRIBUTING.md for development setup.

# 🙏 Credits

Landing page template by ArtleSa (u/ArtleSa)

# License

MIT

查看源码项目主页