wiggitywhitney
MCP Serverwiggitywhitneypublic

vibe_practice

个人沙盒项目,探索使用 Cursor 和 MCP 工具的现代 AI 辅助开发流程。

Repository Info

0
Stars
0
Forks
0
Watchers
0
Issues
JavaScript
Language
-
License

About This Server

个人沙盒项目,探索使用 Cursor 和 MCP 工具的现代 AI 辅助开发流程。

Model Context Protocol (MCP) - This server can be integrated with AI applications to provide additional context and capabilities, enabling enhanced AI interactions and functionality.

Documentation

Vibe Practice 🕸️🌈

Rainbow Background

Welcome to Vibe Practice! This repository is primarily a personal sandbox for exploring and refining modern AI-assisted development workflows, particularly using Cursor and various MCP server integrations.

Primary Goals:

  1. Explore AI Development Tools: Deeply investigate the capabilities of Cursor, Taskmaster-AI, Context7, and MCP Memory within a practical development context.
  2. Refine AI Workflows: Experiment with different approaches to planning, coding, testing, and documentation when heavily leveraging AI assistance.
  3. (Context): Build a simple React 19/Vite application (the 'spider button' app) as the testbed for these explorations.

🤔 What is This Project Really About?

This repository serves as a living laboratory focused on:

  • Cursor Integration: Pushing the boundaries of using Cursor for code generation, refactoring, rule adherence (.cursor/rules), and overall development assistance.
  • MCP Server Experimentation: Actively using and testing MCP server tools, specifically:
    • Taskmaster-AI: For AI-driven project planning, task breakdown, and status tracking (tasks/tasks.json - Note: This file might be in .gitignore). See .cursor/rules/taskmaster.mdc.
    • Context7: For leveraging real-time documentation lookups during development.
    • MCP Memory: For storing and retrieving project context and preferences within the AI's knowledge graph.
  • Workflow Optimization: Finding efficient and effective ways to combine these AI tools into a cohesive development process.
  • TDD with AI: Exploring how Test-Driven Development interacts with AI-assisted coding.

The simple React app (spider button, rainbow) exists mainly to provide concrete tasks and codebases for these AI tooling experiments.


✨ Key Aspects (Focus: AI Tooling)

  • AI-Driven Development: Heavy reliance on Cursor, Taskmaster, Context7, and MCP Memory.
  • Custom AI Configuration: Project-specific Cursor rules (.cursor/rules/) and preferences (docs/preferences.md) guide the AI.
  • Taskmaster Project Management: Utilizing AI for task generation, expansion, and updates.
  • Contextual Documentation: Using Context7 for library/framework information.
  • Test-Driven Development (TDD): Core practice using Jest & React Testing Library, explored alongside AI tools.
  • DevOps Principles: Basic health checks (/server), signal handling applied as relevant context.

(The project also includes an engineering journal system, primarily for logging experiments and observations during this process. See docs/journal/JOURNAL_SYSTEM.md for details.)


🚀 Getting Started (If you really want to run it)

This is mainly a personal exploration project, but if you want to run the React app testbed:

Prerequisites

  • Node.js (LTS version recommended)
  • npm (comes with Node.js)
  • Git

Installation

# 1. Clone the repository
git clone https://github.com/wiggitywhitney/vibe_practice.git

# 2. Navigate into the project directory
cd vibe_practice

# 3. Install dependencies
npm install

Running the App

# Start the development server (usually on http://localhost:8080)
npm run dev

🛠️ Available Scripts

(These are standard Node/React scripts, plus some related to the experimental journal system)

# Start the development server with hot reloading
npm run dev

# Run the test suite once
npm test

# Run tests in interactive watch mode
npm run test:watch

# Start the separate health monitoring server
npm run health

# (For Journal System) Trigger a journal reminder manually
npm run journal:remind

# (For Journal System) Generate weekly journal statistics
npm run journal:stats

workflow Development Workflow Under Test

The core idea is to test an AI-centric workflow:

  1. Planning (Taskmaster): Define goals and let Taskmaster generate/manage tasks.
  2. TDD: Write tests first (Jest/RTL).
  3. Implementation (Cursor): Use Cursor heavily for coding, refactoring, following rules, potentially using Context7 for info.
  4. Verification: Run tests, visual checks.
  5. Logging (Journal): Document findings, especially regarding the AI tools and workflow.
  6. Iteration (Taskmaster/Cursor): Update tasks based on discoveries, refine code.

See Development Workflow and Taskmaster Rules for the specific process being tested.


📚 Key Files for Understanding the Experiment

  • Cursor Rules & Preferences: .cursor/rules/, docs/preferences.md
  • Taskmaster Integration: .cursor/rules/taskmaster.mdc
  • Workflow Documentation: .cursor/rules/dev_workflow.mdc
  • Experiment Logbook: docs/journal/engineering-journal.md

Happy experimenting! 🕷️

Quick Start

1

Clone the repository

git clone https://github.com/wiggitywhitney/vibe_practice
2

Install dependencies

cd vibe_practice
npm install
3

Follow the documentation

Check the repository's README.md file for specific installation and usage instructions.

Repository Details

Ownerwiggitywhitney
Repovibe_practice
LanguageJavaScript
License-
Last fetched8/10/2025

Recommended MCP Servers

💬

Discord MCP

Enable AI assistants to seamlessly interact with Discord servers, channels, and messages.

integrationsdiscordchat
🔗

Knit MCP

Connect AI agents to 200+ SaaS applications and automate workflows.

integrationsautomationsaas
🕷️

Apify MCP Server

Deploy and interact with Apify actors for web scraping and data extraction.

apifycrawlerdata
🌐

BrowserStack MCP

BrowserStack MCP Server for automated testing across multiple browsers.

testingqabrowsers

Zapier MCP

A Zapier server that provides automation capabilities for various apps.

zapierautomation