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# MCP Data Analyzer

## Features

*   **Data Loading and Analysis**: Supports loading `.xlsx` and `.csv` files for statistical analysis.
*   **Visualization**: Generate various graphs and charts using `matplotlib` and `plotly`.

## Installation

To install this project, clone the repository using git:

```bash
git clone https://github.com/OuchiniKaeru/mcp-data-analyzer.git
cd mcp-data-analyzer
uv sync
```

### Development (Unpublished Servers)
```json
"mcpServers": {
  "mcp-data-analyzer": {
    "disabled": false,
    "timeout": 60,
    "type": "stdio",
    "command": "uv",
    "args": [
      "--directory",
      "/path_to/mcp-data-analyzer/",
      "run",
      "mcp-data-analyzer"
    ]
  }
}
```

### Published Servers
```json
"mcpServers": {
  "mcp-data-analyzer": {
    "command": "uvx",
    "args": [
      "mcp-data-analyzer"
    ]
  }
}
```

## 機能

*   **データ読み込みと分析**: `.xlsx` および `.csv` ファイルの読み込みと統計分析をサポートします。
*   **可視化**: `matplotlib` および `plotly` を使用して、さまざまなグラフやチャートを生成します。

## インストール

このプロジェクトをインストールするには、git を使用してリポジトリをクローンします。

```bash
git clone https://github.com/OuchiniKaeru/mcp-data-analyzer.git
cd mcp-data-analyzer
uv sync
```

### 開発 (未公開サーバー)
```json
"mcpServers": {
  "mcp-data-analyzer": {
    "disabled": false,
    "timeout": 60,
    "type": "stdio",
    "command": "uv",
    "args": [
      "--directory",
      "/path_to/mcp-data-analyzer/",
      "run",
      "mcp-data-analyzer"
    ]
  }
}
```

### 公開サーバー
```json
"mcpServers": {
  "mcp-data-analyzer": {
    "command": "uvx",
    "args": [
      "mcp-data-analyzer"
    ]
  }
}
```

TDQS

A3.5/5.0

Scored across 2 tools

Disambiguation5/5

The two tools have completely distinct purposes: load_file is for loading data files into DataFrames, while run_script is for executing Python scripts for analytics tasks. There is no overlap in functionality or ambiguity about when to use each tool.

Naming Consistency4/5

Both tools use snake_case naming, which is consistent. However, load_file follows a verb_noun pattern while run_script uses verb_noun, but the noun 'script' is less specific than 'file', creating a minor deviation in clarity. Overall, the naming is mostly predictable and readable.

Tool Count2/5

With only 2 tools, the server feels severely under-scoped for a 'Data Analyzer' purpose. Key operations like data transformation, filtering, aggregation, or visualization-specific tools are missing, making it inadequate for comprehensive data analysis workflows.

Completeness2/5

The tool set is significantly incomplete for data analysis. While loading and script execution are covered, there are major gaps: no tools for data cleaning, transformation, statistical analysis, or dedicated visualization. This will likely cause agent failures when trying to perform common analytics tasks beyond basic loading and scripting.

Maintenance

ActivityInactive
ResponsivenessNo issues