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 → Build → Understand → Improve → 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:
| Server | Purpose | Status | Connection |
|---|---|---|---|
mcp-vibes-server | Shell access, container management | ✅ Active | Docker exec |
mcp-openmemory-server | Persistent conversation memory | ✅ Active | HTTP (port 8765) |
mcp-basic-memory-server | Knowledge management system | ✅ Active | Docker exec |
mcp-github-server | Repository integration | ✅ Active | Docker exec |
mcp-azure-server | Cloud operations | ✅ Active | Docker exec |
mcp-terraform-server | Infrastructure as code | ✅ Active | Docker exec |
mcp-browserless-server | Browser automation, screenshots | 🔧 Available | Docker exec |
mcp-time-server | Time and timezone functionality | 🔧 Available | Docker exec |
mcp-vibesbox-server | Unified shell + VNC GUI (planned) | 🚧 Development | Docker exec |
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": {
"vibes": {
"command": "docker",
"args": ["exec", "-i", "mcp-vibes-server", "python3", "/workspace/server.py"]
}
}
}
4. Restart Claude Desktop
After updating the configuration, restart Claude Desktop to load the MCP servers.
Current Capabilities
- Execute code in safe, isolated environments
- Remember conversations and build knowledge over time
- Analyze repositories from GitHub
- Manage cloud infrastructure with Azure and Terraform
- Persistent knowledge across sessions
- Browser automation and screenshot capture (optional)
- Learn through conversation rather than documentation
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.