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MCP Server: Local AI Tooling with Python

@Hassenamri005

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Hassenamri005

MCP Server: Local AI Tooling with Python について

An MCP server that reads a CSV file.

MCP Server: Local AI Tooling with Python の設定

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": {
    "mcp-server-example-hassenamri005": {
      "command": "uv",
      "args": [
        "venv"
      ]
    }
  }
}

MCP Server: Local AI Tooling with Python のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

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 🧠 MCP Server: Local AI Tooling with Python?

This project sets up a lightweight Model Context Protocol (MCP) server using Python, enabling AI assistants like Claude to interact with local data files such as CSV and Parquet. By integrating with Claude for Desktop, you can perform tasks like summarizing datasets or retrieving specific information through natural language queries.

How to use 🧠 MCP Server: Local AI Tooling with Python?

Install uv, clone the repository, create a virtual environment, and install dependencies (mcp[cli], pandas, pyarrow). Then add a configuration entry to your Claude Desktop settings with absolute paths to the Python interpreter and mix_server.py. Once configured, use natural language prompts such as "Summarize the contents of data.csv" to interact with your data.

Key features of 🧠 MCP Server: Local AI Tooling with Python

  • Local MCP server (mix_server) for Claude communication
  • CSV and Parquet readers for tabular data
  • Modular structure for easy tool expansion
  • Seamless integration with Claude for Desktop

Use cases of 🧠 MCP Server: Local AI Tooling with Python

  • Summarize the contents of a CSV file
  • Retrieve row and column counts from a Parquet dataset
  • Query specific information from local tabular data via natural language

よくある質問

1

What are the dependencies and runtime requirements?

The server requires Python, `uv` (a fast Python package manager), and the packages `mcp[cli]`, `pandas`, and `pyarrow`. A virtual environment is recommended.

2

What data formats are supported?

The server includes dedicated tools for reading CSV and Parquet files, two common tabular data formats used in data analysis.

3

How do I configure the server with Claude Desktop?

Add a JSON block to your Claude Desktop settings with the `command` pointing to your Python interpreter and `args` including the absolute path to `mix_server.py`. Exact instructions are provided in the README.

4

Is this project open source?

Yes, it is licensed under the MIT License.

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