What are the system requirements?
Python 3.8 or higher and an OpenAI API key. All other dependencies are listed in `requirements.txt`.
@Edwin1719
Basic information
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.
No standard config provided
This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.
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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.
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.
Python 3.8 or higher and an OpenAI API key. All other dependencies are listed in `requirements.txt`.
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.
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.
Yes. The `.env` file must contain a valid `OPENAI_API_KEY` for the NLP‑driven analysis tools to work.
MIT License – see the LICENSE file in the repository for full terms.

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