EuConquisto Composer MCP

# Resource Constraints Assessment ## Task Overview **Assigned to**: Claude Desktop **Priority**: High **Timeline**: Strategic planning phase **Dependencies**: None ## Objective Determine the server resource requirements and deployment constraints for the EuConquisto Composer MCP server to inform architectural decisions and scalability planning. ## Background Context The MCP server uses Playwright browser automation which has significant resource requirements. Current implementation shows: - Browser automation with Chromium instances - Potential memory leaks in long-running scenarios - No resource pooling or cleanup strategies - Unknown server environment constraints ## Key Questions to Address ### 1. Server Environment Constraints - What server resources are available for deployment? - Memory limitations for browser automation - CPU constraints for Chromium instances - Network bandwidth considerations - Operating system and containerization support ### 2. Browser Automation Resource Requirements - How many concurrent browser instances can be supported? - Memory usage per Chromium instance (~100-200MB typical) - Browser lifecycle management requirements - Resource cleanup strategies needed ### 3. Scalability Considerations - Expected concurrent user load - Peak usage patterns - Horizontal vs vertical scaling options - Load balancing requirements ### 4. Performance Targets - Acceptable response times for composition creation - Maximum timeout thresholds - Resource usage monitoring requirements - Performance degradation thresholds ## Deliverables Expected ### 1. Resource Requirements Document - Minimum server specifications - Recommended server configurations - Memory and CPU requirements per concurrent user - Network and storage requirements ### 2. Deployment Architecture Recommendations - Containerization strategy (Docker/Kubernetes) - Resource pooling approaches - Monitoring and alerting requirements - Auto-scaling policies ### 3. Performance Constraints - Maximum concurrent users supported - Response time targets - Resource usage thresholds - Failover and recovery strategies ## Technical Considerations ### Current Implementation Issues - No browser instance pooling - Missing resource cleanup in error scenarios - Potential memory leaks in long-running processes - No connection limits or queuing ### Proposed Solutions to Evaluate - Browser instance pooling with max limits - Resource cleanup with timeouts - Connection queuing for high load - Health checks and auto-recovery ## Success Criteria - [ ] Clear resource requirements documented - [ ] Deployment architecture defined - [ ] Performance targets established - [ ] Monitoring strategy outlined - [ ] Scaling plan created ## Follow-up Actions Results will inform: - Browser automation architecture decisions - Deployment environment selection - Performance optimization priorities - Infrastructure provisioning requirements --- **Note**: This assessment is critical for determining the feasibility of the current browser automation approach and planning the production deployment strategy.