payroll-normalizer-mcp
Allows Windsurf (powered by Codeium) to normalize payroll data from various formats into a standard template
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@payroll-normalizer-mcpNormalize payroll spreadsheets in ~/Downloads/payrolls"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
payroll-normalizer-mcp
让任意支持 MCP 的 AI 工具(Claude Code / Claude Desktop / Cursor / Windsurf / Cline / Zed / 支持 MCP 的 ChatGPT 等)都能把五花八门的工资表一键整理成「社保测算标准模板」。
把企业各种格式的工资表(.xlsx/.xls/.csv,多主体多月份)按"自然人跨主体跨月"归并,自动识别列名、把实发换算回应发(税前),输出 10 列标准模板 + 整理报告。遇到非标表头时,AI 客户端可先 inspect_payroll 看表头样本、判断列含义,再带 overrides 调 normalize_payroll。
工具(MCP tools)
工具 | 作用 |
| 返回标准 10 列定义、身份类型可选值、应发≠实发等口径(映射前先读) |
| 逐文件返回表头、前 3 行样本、自动识别的字段映射、应发口径与问题 |
| 整理为标准模板 xlsx + 报告 md; |
| 生成带下拉+说明的空白标准模板 |
Related MCP server: Excel MCP Server
安装:在各家工具里加这个 MCP server
无需先发布到 PyPI——用 uvx 直接从 GitHub 运行(需本机有 uv)。通用配置:
{
"mcpServers": {
"payroll-normalizer": {
"command": "uvx",
"args": ["--from", "git+https://github.com/dingxiang-me/payroll-normalizer-mcp", "payroll-normalizer-mcp"]
}
}
}放到对应位置即可:
Claude Code(一条命令):
claude mcp add payroll-normalizer -- uvx --from git+https://github.com/dingxiang-me/payroll-normalizer-mcp payroll-normalizer-mcpClaude Desktop:
claude_desktop_config.json→mcpServers(路径见 Settings › Developer)。Cursor:项目根
.cursor/mcp.json(或全局~/.cursor/mcp.json)→ 同上mcpServers。Windsurf:
~/.codeium/windsurf/mcp_config.json→ 同上。Cline / Zed / 其他:填到各自的 MCP 配置里,
command/args一致。
想更快启动可先发布到 PyPI,再把
args换成["payroll-normalizer-mcp"]。
用法
配置好后,直接对 AI 说:
「把
/path/to/工资表文件夹里的工资表整理成社保测算标准模板」
AI 会自动调用 inspect_payroll →(必要时)判断非标列 → normalize_payroll,在该文件夹产出 社保测算标准模板_整理结果.xlsx 和 整理报告.md。
依赖
uv(提供
uvx)运行时自动拉取
mcp、openpyxl;旧版.xls另需xlrd(或先另存为 .xlsx)
配套
产出的标准模板可直接导入「社保公积金薪酬优化测算工具」做测算。本服务只做数据整理,不做社保/个税计算。
许可
MIT
Maintenance
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