mcp-data-wrangler: MCP server for Data Wrangling

Name: mcp-data-wrangler: MCP server for Data Wrangling
Author: shibuiwilliam

@shibuiwilliam

Repository

About mcp-data-wrangler: MCP server for Data Wrangling

No overview available yet

#mcp-server #data-wrangler #data-preprocessing

Basic information

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "mcp-server-data-wrangler": {
      "command": "npx",
      "args": [
        "@modelcontextprotocol/inspector",
        "uv",
        "--directory=src/mcp_data_wrangler",
        "run",
        "mcp-data-wrangler"
      ]
    }
  }
}

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is mcp-data-wrangler?

mcp-data-wrangler is a Model Context Protocol server for data wrangling. It provides a standardized interface for data preprocessing, transformation, and analysis tasks, enabling seamless integration of these operations into the MCP ecosystem.

How to use mcp-data-wrangler?

Clone the repository, then launch the MCP inspector with npx @modelcontextprotocol/inspector uv --directory=src/mcp_data_wrangler run mcp-data-wrangler. Alternatively, add the server to your MCP configuration using the uv command with the --directory argument pointing to the cloned path.

Key features of mcp-data-wrangler

Data aggregation
Descriptive statistics

Use cases of mcp-data-wrangler

Preprocessing data within an MCP-integrated workflow
Performing aggregation operations on structured datasets
Computing descriptive statistics for data summaries and analysis

FAQ from mcp-data-wrangler

—

Comments

More Data & Analytics MCP servers

mcp-server-apache-airflow

yangkyeongmo

169

Google Analytics MCP Server

surendranb

Google Analytics 4 data to AI agents, agentic workflows, and MCP clients. Give agents analysis-ready access to website traffic, user behavior, and performance data with schema discovery, server-side aggregation, and safe defaults that reduce data wrangling.

225