Portfolio Data Analytics MCP Server
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., "@Portfolio Data Analytics MCP Serverload the attached CSV and show me summary statistics"
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.
Python Portfolio — Data Analytics MCP Server
A self-contained demo portfolio project built to showcase Python skills relevant to a data-analytics / AI-assisted development role.
It is a working MCP (Model Context Protocol) server that exposes data analytics tools — load a CSV, compute summary statistics, filter rows, rank columns, compute correlations. An AI assistant (or any MCP client) can drive it over the standard protocol.
Why an MCP server? This is a real, production-shaped type of software: it connects AI agents to tools and data. I build MCP servers and AI agents as part of my daily work, and this project demonstrates those exact skills in a clean, self-contained way.
Features
load_csv— ingest a CSV dataset, get back its inferred schemalist_datasets— show all registered datasetssummary— pandasdescribe()statisticsfilter_rows— filter on a numeric column (>,<,>=, …)top_rows— top-N rows by a numeric columncorrelation— Pearson correlation between two columns
A built-in demo dataset (campaigns) lets it run immediately with no setup.
Related MCP server: DataBeak
Quickstart
# 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 8765Test with the mcp CLI
# register the server so an MCP client can connect
uv run mcp install portfolio_data_mcp.py --name "portfolio-data"Example
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
"Then from an MCP client:
tools: load_csv(name="x", csv_text=...) -> schema
summary(name="x") -> statistics
top_rows(name="x", column="spend", n=3)Project layout
python-portfolio/
├── portfolio_data_mcp.py # the MCP server (tools + logic)
├── tests/
│ └── test_portfolio_mcp.py # 13 passing tests
├── pyproject.toml
└── README.mdTech
Python · MCP SDK (mcp) · pandas · pytest · type hints · uv
© Volodymyr — Vienna, Austria. Part of my job-search portfolio.
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