Datax MCP Server

Datax MCP Server

By haobosang GitHub

Datax is an intelligent data analysis tool designed for the AI era, enabling users to interact with data through natural language to effortlessly gain deep business insights and predictive analytics.

datax data-analysis
Overview

What is Datax MCP Server?

Datax MCP Server is an intelligent data analysis tool designed for the AI era, allowing users to interact with data through natural language to gain deep business insights and predictive analytics effortlessly.

How to use Datax MCP Server?

To use Datax MCP Server, follow these steps:

  1. Initialize the project with uv init.
  2. Create a virtual environment with uv venv.
  3. Activate the virtual environment using source .venv/bin/activate.
  4. Add the default index with uv add --default-index https://pypi.tuna.tsinghua.edu.cn/simple requests.
  5. Install necessary packages with uv add requests fastmcp.
  6. Run the server using uv run server.py.

Key features of Datax MCP Server?

  • Natural language data interaction for intuitive analysis.
  • Deep business insights generation.
  • Predictive analytics capabilities.

Use cases of Datax MCP Server?

  1. Analyzing customer data to identify trends and patterns.
  2. Generating predictive models for sales forecasting.
  3. Enhancing decision-making processes through data-driven insights.

FAQ from Datax MCP Server?

  • Can Datax handle large datasets?

Yes, Datax is designed to efficiently process and analyze large datasets.

  • Is Datax free to use?

The licensing details can be found in the repository, but it is open-source under the Apache-2.0 license.

  • What programming language is Datax built with?

Datax is built using Python.

Content

Datax MCP Server

Datax is an intelligent data analysis tool designed for the AI era, enabling users to interact with data through natural language to effortlessly gain deep business insights and predictive analytics.

✨ Core Features

  • 🔎 Data Search:

How to Use

uv init

uv venv

source .venv/bin/activate

uv add --default-index https://pypi.tuna.tsinghua.edu.cn/simple requests

uv add requests fastmcp

uv run server.py

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