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MCP Data Analytics Server

@Edwin1719

Repository

Basic information

Category

Data & Analytics

License

MIT license

Transports

stdio

Author

Edwin1719

About MCP Data Analytics Server

Un potente servidor de análisis de datos construido con FastMCP que proporciona herramientas especializadas para el procesamiento, análisis y visualización de datos, accesible a través de una interfaz web moderna construida con Streamlit.

MCP Data Analytics Server config

No standard config provided

This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.

Repository

MCP Data Analytics Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is 🔧 MCP Data Analytics Server?

It is an MCP (Model Context Protocol) server built with FastMCP that provides tools for file processing, statistical data analysis, interactive visualization with Plotly, and web tasks like GitHub search and scraping. It exposes a Streamlit web interface for natural‑language interaction, targeting data analysts and developers who want to automate analysis workflows.

How to use 🔧 MCP Data Analytics Server?

Clone the repository, install Python dependencies via pip install -r requirements.txt, copy .env.example to .env and add your OpenAI API key. Run the MCP server with python server.py and the Streamlit client with streamlit run app.py, then open http://localhost:8501. Use natural language prompts to invoke one of the eleven built‑in tools.

Key features of 🔧 MCP Data Analytics Server

  • File management: analysis, creation, and reading of documents.
  • Data analysis: statistics, pivot tables, and type detection.
  • Interactive visualizations using Plotly (bar, line, etc.).
  • Web tools: GitHub repository search and web scraping.
  • Format conversion between CSV, JSON, Excel, and Parquet.

Use cases of 🔧 MCP Data Analytics Server

  • Analyze a sales CSV and view summary statistics.
  • Create a bar chart of monthly sales data.
  • Search GitHub for Python data‑analysis repositories.
  • Convert an Excel file to JSON format for further processing.

Frequently asked questions

1

What are the system requirements?

Python 3.8 or higher and an OpenAI API key. All other dependencies are listed in `requirements.txt`.

2

How do I install and run the server?

Clone the repo, install requirements, configure the `.env` file with your OpenAI API key, then run `python server.py` and `streamlit run app.py` in separate terminals.

3

What tools are included?

Eleven tools: file analysis/creation, PDF/TXT/CSV reading, statistical analysis, advanced pivot tables, Plotly visualization, GitHub repo search, CSS‑based web scraping, URL file download, and data‑format conversion.

4

Does the server require an OpenAI API key?

Yes. The `.env` file must contain a valid `OPENAI_API_KEY` for the NLP‑driven analysis tools to work.

5

What license is the project under?

MIT License – see the LICENSE file in the repository for full terms.

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