BI Chart MCP Server

Name: BI Chart MCP Server
Author: c-cf

@c-cf

BI Chart MCP Server について

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.

基本情報

カテゴリ

データと分析

ライセンス

Apache-2.0

ランタイム

python

トランスポート

stdio

公開者

c-cf

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "bi-chart-mcp-server": {
      "command": "python",
      "args": [
        "-m",
        "mcp_bi_visualizer.server"
      ]
    }
  }
}

ツール

ツールは検出されませんでした

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

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.txt and pyproject.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.