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
Working Components:
- Shell access and code execution in isolated containers
- Persistent memory across conversations via vector database
- Repository analysis and code understanding
- INMPARA knowledge management system
- Azure, Terraform, and GitHub integrations
Architecture: Claude Desktop + MCP servers + Docker containers + Vector DB
Server | Purpose | Status |
---|---|---|
mcp-vibes-server |
Shell access, container management | ✅ Production |
mcp-notebook-server |
INMPARA knowledge management | ✅ Production |
mcp-openmemory-server |
Persistent conversation memory | ✅ Production |
mcp-github-server |
Repository integration | ✅ Production |
mcp-azure-server |
Cloud operations | ✅ Production |
mcp-terraform-server |
Infrastructure as code | ✅ Production |
deepwiki-server |
Code analysis | ✅ Production |
Expanding toward observable AI execution and team collaboration:
Phase 1: Observable Agent Execution
- 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
git clone https://github.com/jonhill90/vibes.git
cd mcp/mcp-vibes-server
docker network create vibes-network
docker-compose up -d
- 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"]
}
}
}
- Execute code in safe, isolated environments
- Remember conversations and build knowledge over time
- Analyze any GitHub repository
- Build real projects with infrastructure automation
- Learn through hands-on conversation rather than documentation
Conversational development environment in production. Observable AI execution in development.