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本周新增
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许可证
MIT

星标增长

每根柱子是这个周期记录下来的 star 增长:优先取逐个 stargazer 到达时间分桶的到达数,还没被 stargazer 扫描覆盖的仓库改用该周期的 star 净增;两个写者都没记录的周期画成虚线空档,而不是当成 0。柱高按各自窗口的峰值归一,两张图不共用坐标轴。指向任意一根柱子, tooltip 里是该周期的九项指标:当前值与周期内的净增。

还没有日粒度数据。每次采集会补齐最近 90 天,下一次采集后这里才会有曲线。

证据时间轴

这个项目还没有记录到异动、发布或许可证变化。

README
The document stored for this repository, with its Chinese translation when one has been produced

MCP Server for Data Exploration

MCP Server is a versatile tool designed for interactive data exploration.

Your personal Data Scientist assistant, turning complex datasets into clear, actionable insights.

mcp-server-data-exploration MCP server

🚀 Try it Out

  1. Download Claude Desktop

  2. Install and Set Up

    • On macOS, run the following command in your terminal:
    python setup.py
    
  3. Load Templates and Tools

    • Once the server is running, wait for the prompt template and tools to load in Claude Desktop.
  4. Start Exploring

    • Select the explore-data prompt template from MCP
    • Begin your conversation by providing the required inputs:
      • csv_path: Local path to the CSV file
      • topic: The topic of exploration (e.g., "Weather patterns in New York" or "Housing prices in California")

Examples

These are examples of how you can use MCP Server to explore data without any human intervention.

Case 1: California Real Estate Listing Prices

  • Kaggle Dataset: USA Real Estate Dataset
  • Size: 2,226,382 entries (178.9 MB)
  • Topic: Housing price trends in California

Watch the video

Case 2: Weather in London

📦 Components

Prompts

  • explore-data: Tailored for data exploration tasks

Tools

  1. load-csv

    • Function: Loads a CSV file into a DataFrame
    • Arguments:
      • csv_path (string, required): Path to the CSV file
      • df_name (string, optional): Name for the DataFrame. Defaults to df_1, df_2, etc., if not provided
  2. run-script

    • Function: Executes a Python script
    • Arguments:
      • script (string, required): The script to execute

⚙️ Modifying the Server

Claude Desktop Configurations

  • macOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%/Claude/claude_desktop_config.json

Development (Unpublished Servers)

"mcpServers": {
  "mcp-server-ds": {
    "command": "uv",
    "args": [
      "--directory",
      "/Users/username/src/mcp-server-ds",
      "run",
      "mcp-server-ds"
    ]
  }
}

Published Servers

"mcpServers": {
  "mcp-server-ds": {
    "command": "uvx",
    "args": [
      "mcp-server-ds"
    ]
  }
}

🛠️ Development

Building and Publishing

  1. Sync Dependencies

    uv sync
    
  2. Build Distributions

    uv build
    

    Generates source and wheel distributions in the dist/ directory.

  3. Publish to PyPI

    uv publish
    

🤝 Contributing

Contributions are welcome! Whether you're fixing bugs, adding features, or improving documentation, your help makes this project better.

Reporting Issues

If you encounter bugs or have suggestions, open an issue in the issues section. Include:

  • Steps to reproduce (if applicable)
  • Expected vs. actual behavior
  • Screenshots or error logs (if relevant)

📜 License

This project is licensed under the MIT License. See the LICENSE file for details.

💬 Get in Touch

Questions? Feedback? Open an issue or reach out to the maintainers. Let's make this project awesome together!

About

This is an open source project run by ReadingPlus.AI LLC. and open to contributions from the entire community.

页面上的每个数字都来自记录下来的 stargazer 到达时间,没有评分公式,也没有 AI 判定。 任何结论都可以用 /api/v1/repos/{id}/stats 里的原始增量自己重算。