BI Chart MCP Server
@c-cf
About BI Chart MCP Server
An MCP (Model Context Protocol) server for data transformation and BI charts will allow AI assistants to connect to your data sources, transform data, and generate high-quality visualizations through natural language requests.
Basic information
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"bi-chart-mcp-server": {
"command": "python",
"args": [
"-m",
"mcp_bi_visualizer.server"
]
}
}
}Tools
No tools detected
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Overview
What is BI Chart MCP Server?
BI Chart MCP Server is a Python‑based implementation of a Model Context Protocol (MCP) server for business intelligence chart visualization. It was migrated from an earlier TypeScript prototype and is intended for developers who need programmatic chart creation within MCP environments.
How to use BI Chart MCP Server?
Clone the repository, create a virtual environment, install dependencies from requirements.txt, then start the server using python scripts/run_server.py or python -m mcp_bi_visualizer.server. Run tests with pytest.
Key features of BI Chart MCP Server
- Built with Python, migrated from TypeScript
- Modular structure: data loading, processing, visualization
- Uses Vega‑Lite for chart rendering
- Includes unit tests for core components
- Configurable via
requirements.txtandpyproject.toml
Use cases of BI Chart MCP Server
- —
FAQ from BI Chart MCP Server
What language is the server written in?
The server is written in Python. The earlier prototype used TypeScript but the maintained version is Python.
How do I install and run the server?
Clone the repo, create a virtual environment, install dependencies, then run via python scripts/run_server.py or python -m mcp_bi_visualizer.server.
Are there tests?
Yes, unit tests are located in the tests/ directory and can be run with pytest.
Does the server have any configuration requirements?
The project uses standard Python configuration files such as requirements.txt, pyproject.toml, and setup.py. Detailed configuration beyond dependency installation is not described in the README.
Is there documentation for contributing?
Yes, the project includes a CONTRIBUTING.md file for guidelines on issues and contributions.
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