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MCP From Zero: Quick Data

@disler

Repository

Basic information

Category

Data & Analytics

Transports

stdio

Author

disler

About MCP From Zero: Quick Data

Prompt focused MCP Server for .json and .csv agentic data analytics for Claude Code

#mathgpt#math-solver#math-assistant

MCP From Zero: Quick Data config

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

{
  "mcpServers": {
    "quick-data-mcp": {
      "command": "uv",
      "args": [
        "run",
        "python",
        "main.py"
      ]
    }
  }
}

MCP From Zero: Quick Data tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

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

Overview

What is MCP From Zero: Quick Data?

MCP From Zero: Quick Data is a Model Context Protocol (MCP) server that enables AI agents to perform arbitrary data analysis on .json and .csv files. It serves as a concrete use case within the "MCP From Zero" learning framework, demonstrating how to combine tools, resources, and prompts into reusable agentic workflows (ADWs).

How to use MCP From Zero: Quick Data?

Navigate to the quick-data-mcp/ directory, copy the sample configuration (.mcp.json.sample to .mcp.json), and update the --directory path to your absolute path. Test the server by running uv run python main.py. Configure your MCP client to point to this server.

Key features of MCP From Zero: Quick Data

  • Perform arbitrary data analysis on JSON and CSV files.
  • Demonstrates the combined use of tools, resources, and prompts.
  • Part of a learning framework for building MCP servers.
  • Quick setup with a sample configuration file.

Use cases of MCP From Zero: Quick Data

  • Learn how to build and scale MCP servers from basic tools to reusable prompts.
  • Provide an AI agent with on-demand analysis of local data files.
  • Experiment with agentic workflows that combine reading, acting, and structured conversations.

Frequently asked questions

1

What programming language and runtime does it require?

The server uses Python. Setup instructions assume the `uv` package manager is installed.

2

How do I connect it to my MCP client?

Copy `.mcp.json.sample` to `.mcp.json`, edit the `--directory` path to your absolute server path, then reference that file in your client’s MCP configuration.

3

What transport protocol does the server use?

The README does not specify the transport; typically MCP servers use stdio or SSE. Check the server’s source code for details.

4

Can the server access files outside the specified directory?

The server is configured with a directory argument. It likely only accesses files within that path, but no explicit restriction is documented.

5

Does the server support authentication?

No authentication mechanism is mentioned in the README.

Comments

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