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Pandas MCP Server

@marlonluo2018

リポジトリ

基本情報

カテゴリ

その他

ライセンス

MIT

トランスポート

stdio

作者

marlonluo2018

Pandas MCP Server について

概要はまだありません

Pandas MCP Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "pandas-mcp-server": {
      "command": "python",
      "args": [
        "cli.py"
      ]
    }
  }
}

Pandas MCP Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is Pandas MCP Server?

A Model Context Protocol (MCP) server that enables LLMs to execute pandas code through a standardized workflow for data analysis and visualization. It provides secure, sandboxed code execution, intelligent data analysis, and interactive chart generation for AI assistants like Claude Desktop.

How to use Pandas MCP Server?

Clone the repository, install dependencies (pip install -r requirements.txt), optionally configure environment variables via .env, and then add a JSON entry to your Claude Desktop configuration (using uvx or python). Verify installation by running python cli.py or python server.py. The server exposes four MCP tools: read_metadata_tool, interpret_column_data, run_pandas_code_tool, and generate_chartjs_tool.

Key features of Pandas MCP Server

  • Sandboxed execution environment for security
  • Automatic file metadata extraction and analysis
  • Interactive Chart.js visualization generation
  • Intelligent memory optimization for large files
  • Easy integration with Claude Desktop
  • Command-line interface for testing and development

Use cases of Pandas MCP Server

  • Let an LLM explore and analyze CSV or Excel files
  • Generate interactive bar, line, or pie charts from data
  • Perform secure, guided data cleaning and transformation
  • Automate multi-step data analysis workflows with AI
  • Interpret categorical columns to improve filtering and aggregation

よくある質問

1

What are the prerequisites to run Pandas MCP Server?

Python 3.10 or higher, pip package manager, and Git are required. Dependencies include `pandas>=2.0.0`, `fastmcp>=1.0.0`, `chardet>=5.0.0`, and `psutil`.

2

What file types does Pandas MCP Server support?

It supports CSV (`.csv`) and Excel (`.xlsx`, `.xls`) files. Excel files can optionally specify a sheet name or index.

3

What tools does the server expose to LLMs?

Four tools: `read_metadata_tool` (file analysis), `interpret_column_data` (column value interpretation), `run_pandas_code_tool` (code execution), and `generate_chartjs_tool` (chart generation).

4

How do I configure Pandas MCP Server with Claude Desktop?

Add a JSON entry with type `"stdio"` and either `"uvx"` (recommended) or `"python"` as the command, pointing to the server directory or `server.py`. The configuration file is located in `%APPDATA%\Claude\claude_desktop_config.json` (Windows), `~/Library/Application Support/Claude/claude_desktop_config.json` (macOS), or `~/.config/Claude/claude_desktop_config.json` (Linux).

5

Is code execution secure in Pandas MCP Server?

Yes, code runs in a sandboxed environment that prevents malicious operations and protects system security.

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