CSV Analyzer MCP Server

by juanmaalt

312 downloads Not rated yet

About

# CSV Analyzer MCP Server A lightweight, modular tool designed to analyze CSV datasets and produce structured summaries suitable for consumption by language models (LLMs) like ChatGPT or Claude. ## Features - **CSV Content Analysis**: Processes CSV data provided as raw content. - **Data Cleaning**: Options to remove…

Explore

- CSV Content Analysis: Processes CSV data provided as raw content.
- Data Cleaning: Options to remove duplicate entries and rows with missing values.
- Flexible Output: Returns results in JSON or Markdown format.
- Customizable Delimiters: Supports various CSV delimiters.

1. Clone the repository:

   git clone https://github.com/juanmaalt/csv_analyzer_mcp_server.git
   cd csv_analyzer_mcp_server
2. Install dependencies using uv:

bash
uv pip install -r requirements.txt
```
_Note: Ensure you have uv installed. If not, refer to the uv installation guide._

A lightweight, modular tool designed to analyze CSV datasets and produce structured summaries suitable for consumption by language models (LLMs) like ChatGPT or Claude.

Features

- CSV Content Analysis: Processes CSV data provided as raw content.
- Data Cleaning: Options to remove duplicate entries and rows with missing values.
- Flexible Output: Returns results in JSON or Markdown format.
- Customizable Delimiters: Supports various CSV delimiters.

Installation

1. Clone the repository:

   git clone https://github.com/juanmaalt/csv_analyzer_mcp_server.git
   cd csv_analyzer_mcp_server
2. Install dependencies using uv:

bash
uv pip install -r requirements.txt
    _Note: Ensure you have uv installed. If not, refer to the uv installation guide._

Usage

The primary function analyze_csv can be invoked with the following parameters: csv_content (str): Raw CSV data as a string. delimiter (str): Delimiter used in the CSV (default: ,). remove_duplicates (bool): Remove duplicate rows (default: True). remove_non_valid_data (bool): Remove rows with missing values (default: True).
  • output_format (str): Output format - 'json' or 'markdown' (default: 'json').

Project Structure

plaintext csv_analyzer_mcp_server/ ├── core/ # Core functionality ├── data/ # Sample CSV files ├── main.py # Entry point ├── pyproject.toml # Project metadata ├── uv.lock # Dependency lock file for uv └── .gitignore # Git ignore rules ```

Contributing

Contributions are welcome! Please fork the repository and submit a pull request.
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