vibes

jonhill90/vibes

3.4

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Vibes is a conversational development environment that leverages distributed MCP servers to transform Claude Desktop into an interactive platform for building and understanding code.

Tools
7
Resources
0
Prompts
0

Ask DeepWiki

Vibes - Conversational Development Environment

Vibes transforms Claude Desktop into a conversational development environment through distributed MCP servers. Instead of learning command-line tools, you describe what you want to build and Claude implements it while teaching you.

Core Philosophy

Ask β†’ Build β†’ Understand β†’ Improve β†’ Create

Current Architecture

Production Stack: Claude Desktop + MCP Servers + Docker Containers + Vector Database

Vibes runs as a distributed system of specialized MCP servers, each handling specific capabilities:

ServerPurposeStatusConnection
mcp-vibes-serverShell access, container managementβœ… ActiveDocker exec
mcp-vibesbox-serverUnified shell + VNC GUIβœ… ActiveDocker exec
basic-memoryPersistent memory across Claude sessionsβœ… ActiveDocker exec
MCP_DOCKERContainer orchestration gatewayβœ… Activedocker mcp
archonTask/knowledge management, RAG searchβœ… Activenpx mcp-remote

Quick Start

Prerequisites

  • Docker Desktop
  • Claude Desktop
  • Git

1. Clone Repository

git clone https://github.com/jonhill90/vibes.git
cd vibes
docker network create vibes-network

2. Start MCP Servers

cd mcp/mcp-vibes-server
docker-compose up -d
cd ..

3. Configure Claude Desktop MCP Settings

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "vibesbox": {
      "command": "docker",
      "args": ["exec", "-i", "mcp-vibesbox-server", "python3", "/workspace/server.py"]
    },
    "basic-memory": {
      "command": "docker",
      "args": ["exec", "-i", "basic-memory-mcp", "/app/start.sh"]
    },
    "MCP_DOCKER": {
      "command": "docker",
      "args": ["mcp", "gateway", "run"]
    },
    "archon": {
      "command": "npx",
      "args": ["mcp-remote", "http://localhost:8051/mcp"]
    }
  }
}

4. Restart Claude Desktop

After updating the configuration, restart Claude Desktop to load the MCP servers.

Current Capabilities

  • Shell execution & container management via mcp-vibes-server MCP

    • Run bash commands in isolated environments
    • Docker container lifecycle management
    • Network access to vibes-network
  • Desktop automation & visual feedback via mcp-vibesbox-server MCP

    • VNC desktop environment (XFCE4, 1920x1080)
    • Screenshot capture for Claude's vision
    • Mouse/keyboard control (click, drag, type)
    • ARM64 Chromium browser automation
  • Task & knowledge management via archon MCP

    • Task tracking (find_tasks, manage_task)
    • RAG search across documentation (2-5 keyword queries)
    • Project management and organization
  • Persistent memory via basic-memory MCP

    • Local Markdown-based knowledge storage
    • Conversation context across sessions
    • Semantic linking and knowledge graphs
  • Container orchestration via MCP_DOCKER gateway

    • Unified MCP server management
    • Security isolation and secrets management
    • Enterprise observability

Context Optimization

We compressed the context Claude sees by 59-70% without losing functionality.

File Sizes Achieved:

  • CLAUDE.md: 107 lines (from 143, 25% reduction)
  • Patterns: 47-150 lines each (target ≀150)
  • Commands: 202-320 lines each (target ≀350)

Context Per Command:

  • /generate-prp: 427 lines (59% reduction from 1044 baseline)
  • /execute-prp: 309 lines (70% reduction from 1044 baseline)

Impact: ~320,400 tokens saved annually (assuming 10 PRP workflows/month)

Why this matters: Claude has an "attention budget"β€”more tokens doesn't mean better results. By compressing context, we improved both speed and accuracy.

See for detailed methodology.

Context Engineering & PRPs

Vibes uses Context Engineering to transform AI coding from generic code generation to production-ready implementation. Instead of prompting in the dark, we engineer comprehensive context that enables first-pass success.

What are PRPs?

PRP (Product Requirements Prompt) = PRD + Curated Codebase Intelligence + Agent Runbook

A PRP is a context engineering artifact that treats Claude like a competent junior developer who needs a comprehensive briefing. It includes:

  • PRD: Clear goals, business value, success criteria
  • Curated Context: Documentation URLs, file references, existing patterns, known gotchas
  • Agent Runbook: Implementation blueprint, pseudocode, task list, validation gates

Naming Convention: PRPs follow a standardized naming convention documented in . Key rules:

  • Use prps/{feature_name}.md (no prp_ prefix)
  • Initial PRPs use INITIAL_ prefix (auto-detected)
  • Directory structure matches feature name

PRP Workflow

1. Create INITIAL.md      β†’ Describe your feature
2. /generate-prp          β†’ Research and create comprehensive PRP
3. /execute-prp           β†’ Implement with validation loops
4. Validation             β†’ Tests pass, code quality verified
5. Done                   β†’ Production-ready code

Directory Structure

vibes/
β”œβ”€β”€ .claude/              # Context-engineered components (59-70% reduction)
β”‚   β”œβ”€β”€ commands/         # Slash commands for Claude Code
β”‚   β”‚   β”œβ”€β”€ generate-prp.md    # 320 lines (59% reduction)
β”‚   β”‚   β”œβ”€β”€ execute-prp.md     # 202 lines (70% reduction)
β”‚   β”‚   β”œβ”€β”€ list-prps.md
β”‚   β”‚   └── prep-parallel.md
β”‚   β”œβ”€β”€ patterns/         # Reusable implementation patterns
β”‚   β”‚   β”œβ”€β”€ README.md          # Pattern library index
β”‚   β”‚   β”œβ”€β”€ archon-workflow.md
β”‚   β”‚   β”œβ”€β”€ parallel-subagents.md
β”‚   β”‚   β”œβ”€β”€ quality-gates.md
β”‚   β”‚   └── security-validation.md
β”‚   β”œβ”€β”€ agents/           # Subagent specifications
β”‚   └── templates/        # Report templates
β”œβ”€β”€ prps/                 # Per-feature PRP artifacts
β”‚   β”œβ”€β”€ {feature_name}/   # Feature-specific directory
β”‚   β”‚   β”œβ”€β”€ planning/     # Research outputs
β”‚   β”‚   β”œβ”€β”€ examples/     # Concrete examples
β”‚   β”‚   └── execution/    # Implementation artifacts
β”‚   └── templates/        # PRP templates
β”‚       β”œβ”€β”€ prp_base.md          # Comprehensive base
β”‚       β”œβ”€β”€ feature_template.md  # Standard features
β”‚       β”œβ”€β”€ tool_template.md     # API integrations
β”‚       └── documentation_template.md
β”œβ”€β”€ CLAUDE.md             # 107 lines (project rules only)
└── mcp/                  # MCP server implementations
    β”œβ”€β”€ mcp-vibesbox-server/
    └── mcp-vibes-server/

Core Principles

  1. Context is King: Include ALL necessary documentation, examples, and gotchas
  2. Validation Loops: Provide executable tests the AI can run and fix iteratively
  3. Information Dense: Use keywords and patterns from your codebase
  4. Progressive Success: Start simple, validate, then enhance
  5. One-Pass Implementation: Comprehensive context enables getting it right the first time

Available Commands

  • /generate-prp <file> - Research codebase and create comprehensive PRP
  • /execute-prp <prp> - Execute PRP with iterative validation
  • /list-prps [status] - List PRPs by status (active/completed/archived)

Example Templates

Choose the right template for your task:

  • Feature Template: Standard feature development
  • Tool Template: API integrations and external tools
  • Documentation Template: READMEs, API docs, guides

Learn More

  • - Comprehensive template with all sections
  • - Reusable implementation patterns
  • Context Engineering Intro - Original philosophy

Philosophy: Context engineering is 10x better than prompt engineering and 100x better than vibe coding. Give Claude the context it needs to succeed.

Pattern Library

The .claude/patterns/ directory contains reusable implementation patterns extracted from the PRP system. These patterns enable consistent, high-quality implementations across all features.

PatternPurposeLink
archon-workflowArchon MCP integration, health checks, graceful degradation
parallel-subagents3x speedup through multi-task parallelization
quality-gatesValidation loops ensuring 8+/10 PRP scores
security-validation5-level security checks for user input

See for complete pattern documentation and usage guidelines.

Future Vision

Phase 1: Observable Agent Execution (In Development)

  • Real-time screen sharing of AI work (terminal, browser, Neovim)
  • Agent-specific environments with persistent state
  • Pause/resume execution controls

Phase 2: Team Collaboration

  • Discord-like interface for human-AI teams
  • Multi-user knowledge spaces
  • Agent coordination visualization

Phase 3: Advanced Intelligence

  • Cross-session agent learning and skill accumulation
  • Intelligent task routing between specialized agents
  • Predictive workflow assistance

Conversational development environment in production. Observable AI execution in development.