Portfolio Data Analytics MCP Server
Python Portfolio — 数据分析 MCP 服务器
一个自包含的演示组合项目,旨在展示与数据分析 / AI辅助开发岗位相关的 Python 技能。
这是一个可运行的 MCP(模型上下文协议)服务器,提供数据分析工具——加载 CSV 文件、计算汇总统计、筛选行、对列排序、计算相关性。AI 助手(或任何 MCP 客户端)可以通过标准协议驱动它。
为什么选择 MCP 服务器? 这是一种真实的、面向生产的软件类型:它将 AI 代理与工具和数据连接起来。我在日常工作中构建 MCP 服务器和 AI 代理,而本项目以简洁、自包含的方式展示了这些核心技能。
功能特性
load_csv— 导入 CSV 数据集,返回推断出的模式list_datasets— 显示所有已注册的数据集summary— pandasdescribe()统计信息filter_rows— 按数值列筛选(>、<、>=等)top_rows— 按数值列取前 N 行correlation— 两列之间的皮尔逊相关系数
内置演示数据集(campaigns)无需任何配置即可立即运行。
Related MCP server: DataBeak
快速开始
# install deps + dev tools
uv sync --dev
# run tests (13 tests covering all tools)
uv run pytest -q
# run as an MCP server over stdio (used by MCP clients)
uv run portfolio_data_mcp.py
# run over SSE for local HTTP testing
uv run portfolio_data_mcp.py --transport sse --port 8765使用 mcp CLI 测试
# register the server so an MCP client can connect
uv run mcp install portfolio_data_mcp.py --name "portfolio-data"示例
echo 'channel,spend,conversions
social,3500,210
search,4200,330
display,3800,95
email,1100,180' | uv run python -c "
import asyncio, portfolio_data_mcp as m
asyncio.run(m.main()) # starts stdio server
"然后从 MCP 客户端:
tools: load_csv(name="x", csv_text=...) -> schema
summary(name="x") -> statistics
top_rows(name="x", column="spend", n=3)项目结构
python-portfolio/
├── portfolio_data_mcp.py # the MCP server (tools + logic)
├── tests/
│ └── test_portfolio_mcp.py # 13 passing tests
├── pyproject.toml
└── README.md技术栈
Python · MCP SDK (mcp) · pandas · pytest · 类型提示 · uv
© Volodymyr — 奥地利维也纳。属于我的求职作品集的一部分。
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