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MCP Servers for CS Experimentation Workshop

from slcc2c

A collection of MCP servers designed for rapid prototyping in CS experimentation workshops.

πŸ”₯πŸ”₯βœ“ VerifiedFreeAdvanced setup

MCP Servers for CS Experimentation Workshop

Achieve "5-minute magic" - go from concept to working experiment in under 5 minutes using AI-collaborative development with Model Context Protocol servers.

Overview

This project implements a comprehensive Model Context Protocol (MCP) server ecosystem designed specifically for rapid CS experimentation. Built for Mac Studio M3 Ultra optimization, it provides seamless integration between AI assistants and development tools.

Features

  • Sub-5-minute Setup: From zero to fully configured development environment
  • Multi-Tier Architecture: Essential, database, and AI collaboration servers
  • Docker Isolation: Secure, containerized environments for each experiment
  • AI Memory: Persistent context across sessions
  • Multi-Database Support: PostgreSQL, Redis, MongoDB, Neo4j out of the box
  • GitHub Integration: Automated repository management and CI/CD
  • TypeScript Build: Clean compilation with full type safety βœ…

Attaching Your Project

Quick Attach (2 minutes)

# Run the interactive attachment script
./scripts/attach-project.sh

# Follow the prompts to:
# 1. Select your project directory
# 2. Choose a project name
# 3. Configure filesystem + memory access

# Restart Claude Desktop and start coding!

πŸ“Ž Read the Project Attachment Guide for detailed instructions and advanced configurations.

Project Templates

Use our pre-configured templates for common project types:

  • Web App: React + Node.js full-stack template
  • API: RESTful API with authentication and docs
  • Data Science: Python ML project with Jupyter
  • Mobile: React Native cross-platform template
# View available templates
ls templates/

# Use a template
cp -r templates/web-app/* /path/to/your/project/

Architecture

Tier 1: Essential Foundation

  • GitHub Server: Repository management, issue tracking, PR automation
  • Filesystem Server: Secure file operations with configurable access
  • Docker Server: Container management and isolated environments
  • Memory Server: Persistent AI context and knowledge graphs

Tier 2: Database & Services

  • PostgreSQL/Supabase: Full database management with real-time features
  • Redis: Caching, sessions, and real-time data structures
  • MongoDB: Document store with Atlas integration
  • Neo4j: Graph database for relationship-heavy experiments
  • Kubernetes: Service orchestration and deployment

Tier 3: AI Collaboration

  • Jupyter Integration: Live notebook execution
  • FastMCP Framework: Rapid tool creation
  • Code Analysis: Automated documentation and insights

Documentation

Documentation