Xiyan_table_mcp_server

Name: Xiyan_table_mcp_server
Author: zyy07

@zyy07

リポジトリ

Xiyan_table_mcp_server について

概要はまだありません

基本情報

カテゴリ

その他

ランタイム

python

トランスポート

stdio

公開者

zyy07

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": {
    "xiyan_table_mcp_server": {
      "command": "python",
      "args": [
        "-m",
        "xiyan_table_mcp_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 Xiyan_table_mcp_server?

Xiyan_table_mcp_server is an MCP server that enables natural language querying of CSV table data using large language models. It supports general LLMs such as GPT and Qwen‑Max, as well as the XiYanTable model, and provides the get_data tool to analyze and respond to natural language questions about table contents.

How to use Xiyan_table_mcp_server?

Install the server via pip: pip install xiyan-table-mcp-server. After installation, create a YAML configuration file (based on the provided config_demo.yml) specifying the CSV path, encoding, preview rows, and model settings. Set the environment variable YML to the config file path, then run the server with python -m xiyan_table_mcp_server. For MCP clients, use the JSON launch configuration shown in the README.

Key features of Xiyan_table_mcp_server

Natural language querying of CSV table data.
Supports GPT, Qwen‑Max, and XiYanTable models.
Reads table contents from CSV files.
Configurable table path, encoding, and preview rows.
Provides a single get_data tool for analysis.
Minimal setup with a YAML configuration file.

Use cases of Xiyan_table_mcp_server

Query CSV data without writing SQL or Python code.
Integrate natural language table analysis into MCP‑compatible applications.
Quickly preview and explore tabular data using conversational AI.
Prototype data‑driven conversations with large language models.

FAQ from Xiyan_table_mcp_server

What Python version is required?

Python 3.10 or higher is required to run the server.

How do I configure the server?

You must provide a YAML configuration file. The README includes a config_demo.yml example that defines the CSV path, encoding, preview row count, model name, API key, API base URL, and temperature.

What language models are supported?

The server supports general LLMs such as GPT and Qwen‑Max, as well as the XiYanTable model. Model details are set via the YAML configuration.

How do I specify the YAML configuration file path?

Set the environment variable YML to the absolute path of your YAML configuration file before starting the server. For example: env YML=path/to/yml python -m xiyan_table_mcp_server.

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