Mcp 伺服器用於數據探索

MCP伺服器數據探索是什麼？

MCP伺服器數據探索是一個由用戶### reading-plus-ai在GitHub上創建的公共庫。這個項目專注於探索MCP伺服器的數據，為用戶提供有效分析和可視化伺服器數據的工具和資源。該庫作為開發者和數據科學家合作、分享見解和增強對伺服器數據動態理解的平台。

MCP伺服器數據探索的特點

• 數據可視化：該庫包含各種可視化伺服器數據的工具，使解釋複雜數據集變得更容易。
• 協作：它鼓勵社區的貢獻，允許用戶分叉庫並添加他們的增強或修改。
• 開源：作為一個公共庫，任何對探索伺服器數據感興趣的人都可以訪問，促進開源環境。
• 文檔：提供全面的文檔，指導用戶如何設置和使用庫中可用的工具。
• 活躍社區：隨著星標和分叉數量的增長，該庫擁有一個活躍的社區，為其開發和改進做出貢獻。

如何使用MCP伺服器數據探索

1. 訪問庫：訪問MCP伺服器數據探索GitHub頁面。
2. 克隆庫：使用Git將庫克隆到本地機器：

   git clone https://github.com/reading-plus-ai/mcp-server-data-exploration.git
   

3. 探索文檔：查看庫內提供的README文件和其他文檔，以了解如何使用工具和功能。
4. 運行工具：按照說明設置並在本地機器上運行數據探索工具。
5. 貢獻：如果您有改進或新功能要添加，隨時分叉庫，進行更改並提交拉取請求。

常見問題

這個庫使用了哪些編程語言？

MCP伺服器數據探索庫主要使用Python進行數據分析和可視化，根據特定工具的需要還使用其他語言。

我可以為MCP伺服器數據探索項目貢獻嗎？

可以！歡迎貢獻。您可以分叉庫，進行更改並提交拉取請求以供審核。

這個庫有許可證嗎？

有的，MCP伺服器數據探索庫根據MIT許可證授權，允許免費使用、修改和分發。

我如何保持對庫變更的更新？

您可以在GitHub上關注該庫，以接收有關更新、問題和項目相關討論的通知。

如果我遇到問題可以在哪裡尋求幫助？

您可以在GitHub庫頁面上打開問題以報告問題或向社區尋求幫助。此外，查看文檔以獲取故障排除提示。

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.

<a href="https://glama.ai/mcp/servers/hwm8j9c422"><img width="380" height="200" src="https://glama.ai/mcp/servers/hwm8j9c422/badge" alt="mcp-server-data-exploration MCP server" /></a>

🚀 Try it Out

1. Download Claude Desktop

   • Get it here

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

• Data Exploration Summary

Case 2: Weather in London

• Kaggle Dataset: 2M+ Daily Weather History UK
• Size: 2,836,186 entries (169.3 MB)
• Topic: Weather in London
• Report: View Report
• Graphs:

  • London Temperature Trends

    <img width="1622" alt="Screenshot 2024-12-09 at 12 48 56 AM" src="https://github.com/user-attachments/assets/9e70fe97-8af7-4221-b1e7-00197c88bb47">

  • Temperature-Humidity Relationship by Season

    <img width="1623" alt="Screenshot 2024-12-09 at 12 47 54 AM" src="https://github.com/user-attachments/assets/f4ac60a8-30e3-4b10-b296-ba412c2922fa">

  • Wind Direction Pattern by Season

    <img width="1622" alt="Screenshot 2024-12-09 at 12 47 00 AM" src="https://github.com/user-attachments/assets/2db01054-f948-4d2e-ba39-8de8fa59f83d">

📦 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.