MCP From Zero: Quick Data

by disler

149 stars

568 downloads

Not rated

GitHub

About

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

Details

Author: disler
GitHub stars: 149
Downloads: 568
Categories: Search

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below

Plugin Name MCP From Zero: Quick Data

Command (node, npx, python, etc.)

Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

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

JSON

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

JSON

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

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

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

JSON

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

JSON

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

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

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

JSON

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

JSON

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

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

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

JSON

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

JSON

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

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

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

JSON

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

JSON

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

From the repository

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.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

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

McpServers

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

MCP From Zero: Quick Data

> Purpose: Learn to build Powerful Model Context Protocol (MCP) servers by scaling tools into reusable agentic workflows (ADWs aka Prompts w/tools).

Quick-Data

> Quick-Data is a MCP server that gives your agent arbitrary data analysis on .json and .csv files. > > We use quick-data as a concrete use case to experiment with the MCP Server elements specifically: Prompts > Tools > Resources. > > See quick-data-mcp for details on the MCP server

MCP Server Prompts

Leading Questions

We experiment with three leading questions:

1. How can we MAXIMIZE the value of custom built MCP servers by using tools, resources, and prompts TOGETHER?
2. What's the BEST codebase architecture for building MCP servers?
3. Can we build an agentic workflow (prompt w/tools) that can be used to rapidly build MCP servers?

Understanding MCP Components

MCP servers have three main building blocks that extend what AI models can do:

Tools

What: Functions that AI models can call to perform actions.

When to use: When you want the AI to DO something at a low to mid atomic level based on your domain specific use cases.

Example:

@mcp.tool()

async def create_task(title: str, description: str) -> dict:

    """Create a new task."""

    # AI can call this to actually create tasks

    return {"id": "123", "title": title, "status": "created"}

Resources

What: Data that AI models can read and access.

When to use: When you want the AI to READ information - user profiles, configuration, status, or any data source.

Example:

@mcp.resource("users://{user_id}/profile")

async def get_user_profile(user_id: str) -> dict:

    """Get user profile by ID."""

    # AI can read this data to understand users

    return {"id": user_id, "name": "John", "role": "developer"}

Prompts

What: Pre-built conversation templates that start specific types of discussions.

When to use: When you want to give the AI structured starting points for common, repeatable workflows for your domain specific use cases.

Example:

@mcp.prompt()

async def code_review(code: str) -> str:

    """Start a code review conversation."""

    # AI gets a structured template for code reviews

    return f"Review this code for security and performance:\n{code}"

Quick Decision Guide

- Need AI to take action? → Use Tools
- Need AI to read data? → Use Resources
- Need Reusable Agentic Workflows (ADWs)? → Use Prompts

Quick Setup

To use the Quick Data MCP server:

1. Navigate to the MCP server directory:

   cd quick-data-mcp/

2. Configure for your MCP client:

   # Copy the sample configuration

   cp .mcp.json.sample .mcp.json

   

   # Edit .mcp.json and update the --directory path to your absolute path

   # Example: "/Users/yourusername/path/to/quick-data-mcp"

3. Test the server:

   uv run python main.py

See quick-data-mcp/README.md for complete setup and usage documentation.

Resources

- MCP Clients: https://modelcontextprotocol.io/clients - Claude Code Resource Support Github Issue: https://github.com/anthropics/claude-code/issuesç/545

Master AI Coding

Learn to code with AI with foundational Principles of AI Coding

Follow the IndyDevDan youtube channel for more AI coding tips and tricks.

Use the best Agentic Coding Tool: Claude Code

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MCP From Zero: Quick Data

About

Details

Jump to

Setting up with Highlight

Setting up with Cursor

JSON

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JSON

Setting up with Claude Desktop

JSON

JSON

JSON

Setting up with Windsurf

JSON

JSON

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Setting up with Cline

JSON

JSON

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Setting up with Goose

JSON

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JSON

From the repository

Claude Desktop / Cursor

McpServers

MCP From Zero: Quick Data

Quick-Data

Leading Questions

Understanding MCP Components

Tools

Resources

Prompts

Quick Decision Guide

Quick Setup

Resources

Master AI Coding

Install

About

Details

Jump to

Setting up with Highlight

From the repository

Claude Desktop / Cursor

McpServers

MCP From Zero: Quick Data

Quick-Data

Leading Questions

Understanding MCP Components

Tools

Resources

Prompts

Quick Decision Guide

Quick Setup

Resources

Master AI Coding

Install

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