Basic MCP Server for Data File Analysis

A Model Context Protocol (MCP) server that provides tools for analyzing CSV and Parquet files.

Features

• CSV File Analysis: Summarize CSV files by reporting row and column counts

• Parquet File Analysis: Summarize Parquet files by reporting row and column counts

• Sample Data: Includes sample user data in both CSV and Parquet formats

Related MCP server: Claude Data Buddy

Project Structure

mix_server/
│
├── data/                 # Sample CSV and Parquet files
│   ├── sample.csv
│   └── sample.parquet
│
├── tools/                # MCP tool definitions
│   ├── __init__.py
│   ├── csv_tools.py
│   └── parquet_tools.py
│
├── utils/                # Reusable file reading logic
│   ├── __init__.py
│   └── file_reader.py
│
├── server.py             # MCP server instance
├── main.py              # Entry point for the MCP server
├── generate_parquet.py  # Script to convert CSV to Parquet
└── README.md            # This file

Installation

1. Install uv (if not already installed):

   curl -LsSf https://astral.sh/uv/install.sh | sh

2. Create and activate virtual environment:

   uv venv
   source .venv/bin/activate

3. Install dependencies:

   uv add "mcp[cli]" pandas pyarrow

Usage

Running the Server

Start the MCP server:

uv run main.py

Using with LM Studio

To use this MCP server with LM Studio, edit your mcp.json file and add:

This starts the MCP server for you.

{
  "mcpServers": {
    "mix_server": {
      "command": "uv",
      "args": [
        "--directory",
        "/path/to/your/mcp_server_public",
        "run",
        "main.py"
      ]
    }
  }
}

Note: Replace /path/to/your/mcp_server_public with the actual path to your mcp_server_public directory.

Once loaded you should see all available tools for your local LLM to use.

Available Tools

1. summarize_csv_file(filename: str)

   • Summarizes a CSV file by reporting its number of rows and columns

   • Example: summarize_csv_file("sample.csv")

2. summarize_parquet_file(filename: str)

   • Summarizes a Parquet file by reporting its number of rows and columns

   • Example: summarize_parquet_file("sample.parquet")

Sample Data

The server includes sample user data with the following structure:

• id: Unique identifier

• name: User's full name

• email: User's email address

• signup_date: Date when the user signed up

Development

Adding New Tools

1. Create a new file in the tools/ directory

2. Import the MCP server instance: from server import mcp

3. Define your tool function with the @mcp.tool() decorator

4. Import the new tool module in main.py

Adding New File Formats

1. Add utility functions in utils/file_reader.py

2. Create corresponding tools in the tools/ directory

3. Import the new tools in main.py

Dependencies

• mcp[cli]: Official MCP SDK and command-line tools

• pandas: For reading CSV and Parquet files

• pyarrow: Adds support for reading Parquet files via Pandas

License

This project is open source and available under the MIT License.