MCP Servers

Sensors MCP Server

Enables AI assistants to query and analyze user behavior data from the Sensors Analytics platform using natural language.

README

Sensors MCP Server

基于 MCP（Model Context Protocol）的神策分析数据服务，让 AI 助手通过自然语言直接查询和分析神策平台中的用户行为数据。

功能概览

工具	说明
`get_sensors_config`	获取当前神策配置信息（调试用）
`verify_sensors_config`	验证 API 连通性和认证有效性
`list_events_all`	获取项目中的全部事件列表
`list_event_tags`	获取事件标签分类信息
`get_event_properties`	获取指定事件的属性定义
`list_event_properties_all`	获取所有事件的属性列表
`query_segmentation_report`	事件分析查询（次数、人数、维度拆分、筛选过滤）

快速开始

1. 安装依赖

npm install

2. 配置环境变量

复制 .env.example 为 .env，填写你的神策分析配置：

cp .env.example .env

SA_URL=https://your-sensors-analytics-url
SA_PROJECT=your_project_name
SA_API_KEY=your_api_key
SA_API_SECRET=your_api_secret  # 可选

API Key 在神策后台「项目管理 → 数据接口」中获取。

3. 编译与启动

# 编译
npm run build

# 生产模式
npm start

# 开发模式（直接运行 TypeScript，改完代码重启即可）
npm run dev

接入 MCP 客户端

QoderWork / Claude Desktop

在 MCP 设置中添加 Server，配置启动命令：

{
  "mcpServers": {
    "sensors": {
      "command": "node",
      "args": ["/path/to/SensorsMCPServer/dist/index.js"],
      "env": {
        "SA_URL": "https://your-sensors-analytics-url",
        "SA_PROJECT": "your_project_name",
        "SA_API_KEY": "your_api_key"
      }
    }
  }
}

MCP Server 使用 stdio 协议通信，由客户端启动和管理进程，无需手动运行。

调试

推荐使用 MCP Inspector 进行调试：

npx @modelcontextprotocol/inspector node dist/index.js

启动后访问 http://localhost:6274，可以手动调用工具、查看请求和响应。

使用示例

接入 MCP 客户端后，直接用自然语言提问即可：

查询上月左侧菜单点击事件的次数和人数

web_workgroup_nav_menu_cli 事件有哪些属性？

查询上月左侧菜单点击情况，按用户和菜单名拆分

AI 会自动探索事件元数据、构建查询参数、调用 API 并解读结果。

项目结构

src/
├── index.ts                 # MCP Server 入口，工具注册与请求路由
├── config.ts                # 环境变量配置管理
└── tools/
    ├── event-meta.ts        # 事件列表与标签查询
    ├── property-meta.ts     # 事件属性查询
    └── segmentation.ts      # 事件分析报告查询

技术栈

运行环境：Node.js（ES2022+）
开发语言：TypeScript 5.x
MCP SDK：@modelcontextprotocol/sdk ^0.6.0
通信协议：stdio
API 规范：神策分析 OpenAPI v3
认证方式：Header 认证（api-key + sensorsdata-project）

License

ISC

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