Summary

Complete production setup with container fixes, serverless optimization, and remote client integration.

Key Improvements

🔧 Container Fixes

• Fixed Playwright browser permissions in both CPU and RunPod containers
• Enhanced RunPod serverless with GPU acceleration and proper user management
• Added missing dependencies to requirements-runpod.txt

🚀 Production Features

• Remote HTTPS access via Nginx proxy with proper endpoint routing
• OpenRouter LLM integration with free model support (qwen/qwq-32b:free)
• GPU acceleration enabled for RunPod serverless ML processing
• Security improvements with non-root user execution

📚 Documentation & Config

• 3 corrected Claude Desktop configs with proper workspace paths
• Comprehensive troubleshooting guides for MCP connection issues
• Complete task documentation following CONDUCTOR.md format
• Updated phase tracking in TASKS.md

Technical Details

Dockerfile Changes

CPU Container (Dockerfile.cpu):

# Fixed: Install browsers as correct user to avoid permission issues
USER mcpuser
RUN playwright install chromium

RunPod Container (Dockerfile.runpod):

# Added: Proper user management and GPU acceleration
RUN groupadd --gid 1000 mcpuser && useradd --uid 1000 --gid mcpuser --shell /bin/bash --create-home mcpuser
USER mcpuser
RUN playwright install chromium
ENV CRAWL4AI_ENABLE_GPU=true

Dependencies

Enhanced requirements-runpod.txt:

playwright>=1.40.0  # Added missing dependency

Configuration Files

• configs/claude_desktop_config_corrected.json - Standard MCP configuration
• configs/claude_desktop_config_pure_http_corrected.json - HTTP transport
• configs/claude_desktop_config_script_corrected.json - Script-based setup

Testing Validation

• ✅ CPU containers build successfully with fixed Playwright permissions
• ✅ RunPod serverless enhanced with GPU acceleration and security
• ✅ MCP remote client connects properly via HTTPS
• ✅ OpenRouter LLM integration working with free models
• ✅ All 19 MCP tools accessible through production pipeline

Production Impact

• Deployment Options: Both CPU-only and GPU-accelerated environments ready
• Remote Access: Full HTTPS access via Nginx proxy with proper routing
• Cost Optimization: Free LLM processing via OpenRouter integration
• Performance: GPU acceleration for ML tasks in serverless environment
• Security: Non-root user execution in both deployment types

This PR completes the production setup phase and enables full remote deployment capabilities.

🤖 Generated with Claude Code