xtai-mcp-data-analysis
一个基于MCP协议的数据分析和可视化 MCP server,支持CSV和Excel格式的数据文件处理。
功能特性
- 数据概览:获取数据的表头信息、字段类型、数据条数等基本信息
- 数据汇总分析:计算数值列的平均值、中位数、方差等统计指标
- 多维数据透视可视化:生成柱状图、饼图、热力图、堆叠图等多种可视化图表
- 灵活的聚合函数:支持求和(sum)、平均(mean)、计数(count)、最大值(max)、最小值(min)等多种聚合方式
如何在客户端引用
在MCP客户端配置中添加如下配置:
{
"mcpServers": {
"xtai-mcp-data-analysis": {
"command": "uvx",
"args": ["xtai-mcp-data-analysis"]
}
}
}
提供的工具
1. data_overview
获取数据的基本概览信息。
参数:
data_path: 数据文件路径,支持.csv、.xlsx、.xls格式
示例:
{
"name": "data_overview",
"arguments": {
"data_path": "./sales_data.csv"
}
}
2. data_summary
获取数据的汇总分析情况,包括数值列统计、类别列统计和缺失值统计。
参数:
data_path: 数据文件路径,支持.csv、.xlsx、.xls格式
示例:
{
"name": "data_summary",
"arguments": {
"data_path": "./sales_data.xlsx"
}
}
3. visualize_data
通过数据透视的方式可视化数据。
参数:
data_path: 数据文件路径,支持.csv、.xlsx、.xls格式index: 数据透视的索引列名列表,支持1-2个维度,如['城市','季度']values: 需要聚合的数值列名列表,如['销量','销售额']aggfunc(可选): 聚合函数,支持sum | mean | count | max | min | median | std | var,默认是sumoutput_dir(可选): 聚合图表的保存目录,默认./output
示例:
{
"name": "visualize_data",
"arguments": {
"data_path": "./sales_data.csv",
"index": ["城市"],
"values": ["销售额"],
"aggfunc": "sum",
"output_dir": "./charts"
}
}
支持的文件格式
- CSV (逗号分隔值文件)
- XLSX (Excel 2007+ 文件)
- XLS (旧版 Excel 文件)
输出图表类型
根据输入参数的不同,服务器会自动生成多种类型的图表:
- 单维度分析:柱状图、饼图
- 双维度分析:热力图、堆叠柱状图、分组柱状图
- 多值对比:多指标对比柱状图
所有生成的图表都会以PNG格式保存到指定的输出目录中,并返回图表路径和对应的数据信息。
Metadata
Release files for xtai-mcp-data-analysis 0.1.0
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Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| xtai_mcp_data_analysis-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 19.0 kB
Release files / xtai_mcp_data_analysis-0.1.0.tar.gz
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