Click on "Deploy 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., "@BI Chart MCP Server create a bar chart of sales by region from sales_data.csv"
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.
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.
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.
Related MCP server: data-analysis-mcp
Clone the repository.
Create a virtual environment and activate it:
python -m venv .venv
.venv\Scripts\activate # On WindowsInstall the required dependencies:
pip install -r requirements.txtYou can run the server using the provided script:
python scripts/run_server.pyAlternatively, you can start the server directly from the module:
python -m mcp_bi_visualizer.serverRun the tests using your preferred test runner. For example, with pytest:
pytestThe 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!
This server cannot be deployed
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