Brummer MCP Server

# Master Request Analysis: Agentic AI Coders in TUI ## Original Request **User Request**: "plan out being able to launch and run agentic ai coders in a tab in the tui" ## Business Context Analysis **Why This Feature is Needed**: - Brummer is a development environment orchestration tool with TUI interface - Current TUI supports process management, logs, and browser automation - Adding AI coders would enable developers to launch autonomous coding agents within their development workflow - This extends Brummer from process orchestration to intelligent development assistance - Fits with the existing MCP (Model Context Protocol) integration for AI tool access ## Success Definition **Feature Complete When**: - [ ] New TUI tab/view for AI coder management - [ ] Can launch multiple AI coder instances - [ ] Each coder has isolated workspace and context - [ ] Integration with existing MCP infrastructure - [ ] Visual status monitoring and control - [ ] Proper resource management and cleanup ## Project Phase Assessment **Current Brummer Maturity**: Production-ready process manager with MCP integration **Feature Complexity**: HIGH - Multiple new subsystems required **Integration Scope**: Cross-system (TUI, MCP, Process Management, File System) ## Timeline Constraints **Development Complexity**: 20-30 hours estimated **Integration Risk**: HIGH - requires coordination across multiple existing systems **User Priority**: Development productivity enhancement ## Integration Scope Analysis **Systems Affected**: - TUI system (new views and tab management) - MCP server infrastructure (new tools and capabilities) - Process management system (AI coder lifecycle) - File system management (workspace isolation) - Configuration system (AI coder settings) - Event system (status updates and communication) ## Feature Architecture Overview **Core Components**: 1. **AI Coder Management Service** - Launch, monitor, and control AI coder instances 2. **TUI Integration** - New tab/view for AI coder interface 3. **Workspace Isolation** - File system sandboxing for AI coder operations 4. **MCP Tool Extensions** - New MCP tools for AI coder interaction 5. **Status Monitoring** - Real-time visibility into AI coder activities 6. **Resource Management** - Memory, CPU, and file system quotas ## Risk Assessment **High Risks**: - AI coder integration complexity - Resource management and isolation - TUI architecture modifications - MCP tool coordination **Medium Risks**: - User experience design - Configuration management - Error handling and recovery **Low Risks**: - Basic process lifecycle management - Logging and monitoring integration