Use This MCP server To

Connect AI assistants to diverse data sources for analysis Transform raw data into structured formats for visualization Generate BI charts from natural language queries Automate report generation with dynamic data visualizations Integrate with AI workflows to enhance data-driven decision making Visualize complex datasets using customizable chart components Test and validate BI visualizations with unit tests

README

BI Chart MCP Server

This project implements the BI Chart MCP Server using Python. Previously, the functionality was prototyped with TypeScript, but the current and maintained version is built with Python.

Project Structure

mcp_bi_visualizer/: Contains the main server code and modules.
- server.py: Main entry point for starting the MCP server.
- data/: Data loading and processing modules.
  - loader.py
  - processor.py
- resources/: Modules to manage project resources.
  - manager.py
  - memo.py
- visualization/: Visualization components.
  - renderer.py
  - vega_lite.py
scripts/
- run_server.py: A script to launch the server.
tests/: Unit tests for the server and visualization components.
Other files include configuration files (e.g., pyproject.toml, requirements.txt, setup.py) and documentation.

Installation

Clone the repository.

Create a virtual environment and activate it:

python -m venv .venv
.venv\Scripts\activate   # On Windows

Install the required dependencies:
```
pip install -r requirements.txt
```

Running the Server

You can run the server using the provided script:

python scripts/run_server.py

Alternatively, you can start the server directly from the module:

python -m mcp_bi_visualizer.server

Testing

Run the tests using your preferred test runner. For example, with pytest:

pytest

Notes

The project has been migrated from a TypeScript-based implementation to Python.
For any issues or contributions, please refer to the CONTRIBUTING.md file.

Enjoy using the BI Chart MCP Server!

BI-Chart-MCP-Server FAQ

How do I install the BI-Chart-MCP-Server?

Clone the repository, create and activate a Python virtual environment, then install dependencies using pip as per the README instructions.

What programming language is the BI-Chart-MCP-Server implemented in?

The server is implemented in Python, with a previous prototype in TypeScript.

How does the server handle data transformation?

It uses modular data loading and processing components to transform raw data into formats suitable for visualization.

Can I customize the visualizations generated by the server?

Yes, the server includes visualization modules like renderer.py and vega_lite.py for customizable chart rendering.

How do I start the MCP server?

Use the provided run_server.py script to launch the MCP server as described in the documentation.

Is there support for testing the server?

Yes, the project includes unit tests for server and visualization components to ensure reliability.

What types of visualizations can the server generate?

The server supports generating BI charts using Vega-Lite specifications and other customizable visualization components.

How does this server integrate with AI assistants?

It exposes data transformation and visualization capabilities via MCP, allowing AI assistants to query and generate charts through natural language.