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CSV Analyzer MCP Server

@juanmaalt

リポジトリ

基本情報

カテゴリ

データと分析

トランスポート

stdio

作者

juanmaalt

CSV Analyzer MCP Server について

概要はまだありません

#csv-analyzer#data-analysis#language-models

CSV Analyzer MCP Server の設定

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このサーバーの README には解析可能な MCP 設定ブロックが含まれていません。インストール手順はリポジトリをご確認ください。

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CSV Analyzer MCP Server のツール

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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 CSV Analyzer MCP Server?

CSV Analyzer MCP Server is a lightweight, modular tool that analyzes CSV datasets and produces structured summaries for consumption by language models like ChatGPT or Claude. It is designed for developers who need to prepare CSV data for LLM processing.

How to use CSV Analyzer MCP Server?

Clone the repository, install dependencies with uv pip install -r requirements.txt, then invoke the analyze_csv function with parameters: csv_content (raw CSV string), delimiter (default ,), remove_duplicates (default True), remove_non_valid_data (default True), and output_format (json or markdown, default json).

Key features of CSV Analyzer MCP Server

  • Processes raw CSV content as a string.
  • Removes duplicate rows and rows with missing values.
  • Returns results in JSON or Markdown format.
  • Supports customizable CSV delimiters.
  • Lightweight and easy to integrate.

Use cases of CSV Analyzer MCP Server

  • Preprocessing CSV data before feeding it to an LLM.
  • Cleaning datasets by removing duplicates and incomplete rows.
  • Converting CSV summaries into structured JSON for downstream tools.
  • Preparing CSV content in Markdown for human-readable LLM prompts.

よくある質問

1

What dependencies are required?

You need Python and `uv` (or `pip`) to install the dependencies listed in `requirements.txt`. The server itself is written in Python.

2

How do I clean the CSV data?

Set `remove_duplicates=True` to drop duplicate rows, and `remove_non_valid_data=True` to drop rows with missing values. Both are `True` by default.

3

What output formats are supported?

The tool returns results in JSON (default) or Markdown, controlled by the `output_format` parameter.

4

Can I use a different delimiter?

Yes, pass the desired delimiter as the `delimiter` parameter; the default is a comma (`,`).

5

How is the CSV data provided to the server?

Data is passed as a raw string via the `csv_content` parameter – no file path or upload is used.

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