Survey Cross-Analysis MCP Server

Survey Cross-Analysis MCP Server

An AI-driven tool for processing survey data that supports cross-tabulation, NPS and satisfaction scoring, and automated Excel report generation. It enables users to analyze datasets via natural language for tasks like merging response options and identifying demographic differences.

Category
Visit Server

README

问卷交叉分析 MCP Server (survey-crosstab)

AI 驱动的问卷数据交叉分析工具,作为 MCP Server 运行,可被 Claude Desktop、Cursor 及其他 MCP 客户端调用。

功能概览

工具 功能
load_survey_data 加载问卷(Excel/CSV),自动识别单选/多选/文本/元数据列
preview_column_data 预览指定列的频数分布
merge_column_options 合并选项(如 1-3 归为"不满意",4-5 归为"满意")
run_crosstab_analysis 执行交叉分析(频数表 + 列百分比)
calc_score_analysis 自动识别计算满意度得分或 NPS(支持 ["auto"] 自动检测)
get_analysis_summary 提取关键差异摘要(辅助 AI 撰写报告)
export_report 导出格式化 Excel(含 DataBar、v3 结构化分析报告 sheet)

安装

方式一:一键安装(推荐)

# 下载 survey-crosstab.exe 后,直接运行:
survey-crosstab.exe install

# 仅配置特定客户端:
survey-crosstab.exe install --client cursor
survey-crosstab.exe install --client claude

安装命令会自动:

  1. 将 exe 复制到 %LOCALAPPDATA%/survey-crosstab/
  2. 检测并配置已安装的 MCP 客户端(Cursor、Claude Desktop)
  3. 输出手动配置说明(适用于其他 MCP 客户端)

方式二:手动配置

在 MCP 客户端的配置界面中填写:

字段
Command C:\Users\你的用户名\AppData\Local\survey-crosstab\survey-crosstab.exe
Args (留空)

或直接编辑 JSON 配置:

{
  "mcpServers": {
    "survey-crosstab": {
      "command": "C:\\Users\\你的用户名\\AppData\\Local\\survey-crosstab\\survey-crosstab.exe",
      "args": [],
      "env": {}
    }
  }
}

方式三:从源码运行

cd MCP-crosstable
pip install -r requirements.txt
python server.py

命令行参考

survey-crosstab.exe                      # 启动 MCP 服务器(stdio 模式)
survey-crosstab.exe --port 8000          # 启动 MCP 服务器(SSE/HTTP 模式)
survey-crosstab.exe install              # 一键安装并配置
survey-crosstab.exe install --client cursor  # 仅配置 Cursor
survey-crosstab.exe uninstall            # 卸载并移除配置
survey-crosstab.exe --version            # 查看版本
survey-crosstab.exe --help               # 查看帮助

使用示例

示例 1:分析性别差异

"帮我加载 survey_90450_w_0.xlsx,然后分析男生女生在各题目上的差异"

AI 会自动:

  1. load_survey_data → 识别数据结构
  2. run_crosstab_analysis(行="all", 列="Q17.性别") → 交叉分析
  3. calc_score_analysis(["auto"]) → 自动检测并计算所有满意度/NPS得分
  4. get_analysis_summary → 获取差异摘要
  5. 撰写分析报告
  6. export_report → 导出 Excel

示例 2:合并选项后分析

"把 Q1 满意度的 1-3 分归为不满意,4-5 分归为满意,然后和其他题目做交叉"

AI 会自动:

  1. load_survey_data → 加载数据
  2. merge_column_options(rules={"不满意":[1,2,3], "满意":[4,5]}) → 合并选项
  3. run_crosstab_analysis(行="all", 列=合并后列名) → 交叉分析
  4. export_report → 导出 Excel

文件结构

MCP-crosstable/
├── server.py              # MCP Server 主入口(7 个工具定义 + CLI 入口)
├── crosstab_engine.py     # 核心数据处理引擎
├── crosstab_export.py     # Excel 导出与样式模块(v3 结构化报告)
├── installer.py           # 安装/卸载模块
├── requirements.txt       # Python 依赖
└── README.md              # 本文件

版本历史

版本 更新内容
v1.1.0 结构化分析报告 sheet (v3)、NPS 百分比格式、满意度双条件自动检测、一键安装
v1.0.0 初始版本:7 个工具、交叉分析、DataBar 可视化

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured