coding-essentials/.env.ports at main · The-Raedical-Co/coding-essentials · GitHub

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# Centralized Port Configuration for Coding Project
# Single source of truth for all service ports

# MCP Servers
# claude-logger-mcp: stdio transport (no port needed)

# ============================================
# Docker Mode MCP SSE Servers
# ============================================
# These ports are used when running in Docker mode (HTTP/SSE transport)
# In native mode, MCP servers use stdio transport (no ports needed)

# Browser Access SSE Server (shared across parallel Claude sessions)
BROWSER_ACCESS_SSE_PORT=3847
# - Provides: Shared MCP server for browser automation via Stagehand
# - Health check: HTTP GET http://localhost:3847/health
# - Architecture: Single SSE server, multiple stdio proxy clients
# - Related: BROWSERBASE_CDP_PORT for Chrome DevTools Protocol

# Semantic Analysis SSE Server (Docker mode)
SEMANTIC_ANALYSIS_SSE_PORT=3848
# - Provides: UKB workflows, knowledge extraction, pattern analysis
# - Health check: HTTP GET http://localhost:3848/health
# - Dependencies: Qdrant (6333), LLM providers

# Constraint Monitor SSE Server (Docker mode)
CONSTRAINT_MONITOR_SSE_PORT=3849
# - Provides: Real-time constraint checking, violation tracking
# - Health check: HTTP GET http://localhost:3849/health
# - Dependencies: Qdrant (6333), Redis (6379)

# Code Graph RAG SSE Server (Docker mode)
CODE_GRAPH_RAG_SSE_PORT=3850
# - Provides: AST-based code analysis, natural language queries
# - Health check: HTTP GET http://localhost:3850/health
# - Dependencies: Memgraph (7687)

# System Health & Monitoring
MONITORING_PORT=9090

# Knowledge Services
VKB_PORT=8080
MEMORY_VISUALIZER_PORT=8080  # Same as VKB, will use port manager to resolve

# Constraint Monitor Services
CONSTRAINT_DASHBOARD_PORT=3030  # Next.js frontend for constraint monitoring
CONSTRAINT_API_PORT=3031        # Express.js API backend for constraint monitoring

# Health Monitoring for Constraint Monitor Services:
# - Port 3030: Dashboard frontend health check via HTTP GET /
# - Port 3031: API backend health check via HTTP GET /api/health
# - Health monitoring ensures proper inter-service communication
# - Dashboard redirects to frontend, API provides data endpoints
# - Both services must be running for full constraint monitoring functionality

# System Health Dashboard Services
SYSTEM_HEALTH_DASHBOARD_PORT=3032  # Next.js frontend for system health monitoring
SYSTEM_HEALTH_API_PORT=3033        # Express.js API backend for system health monitoring

# System Health Monitoring:
# - Port 3032: System health dashboard frontend (databases, services, processes)
# - Port 3033: System health API (verification reports, auto-healing status)
# - Monitors: LevelDB, Qdrant, VKB, Constraint Monitor, Process Registry
# - Provides: Real-time health status, auto-healing actions, violation history

# CoPilot Integration
COPILOT_PORT=8765

# External Service Ports (for reference)
BROWSERBASE_CDP_PORT=9222  # Chrome DevTools Protocol (external)
KNOWLEDGE_SYNC_PORT=3001   # If needed for future sync services

# Service Configuration
# Agent Types: claude, copilot, both
DEFAULT_AGENT_TYPE=claude

# Health Check Configuration
HEALTH_CHECK_TIMEOUT=5000
HEALTH_CHECK_INTERVAL=30000
SERVICE_STARTUP_TIMEOUT=60000
SERVICE_SHUTDOWN_TIMEOUT=30000

# Port Allocation Strategy
# - prefer_configured: Use configured ports, fail if unavailable
# - find_available: Find next available port if configured is taken
# - kill_existing: Kill existing process if it's one of our services
PORT_ALLOCATION_STRATEGY=kill_existing

# Memgraph Database (for code-graph-rag AST knowledge graph)
MEMGRAPH_BOLT_PORT=7687    # Bolt protocol for queries
MEMGRAPH_HTTPS_PORT=7444   # HTTPS interface
MEMGRAPH_LAB_PORT=3100     # Memgraph Lab UI

# Docker Model Runner (local LLM inference via llama.cpp)
DMR_PORT=12434             # OpenAI-compatible API endpoint
DMR_HOST=localhost         # Host for DMR API (see below for Windows)
# - Provides: Local LLM inference using Docker Desktop's Model Runner
# - API: http://localhost:12434/engines/v1 (OpenAI-compatible)
# - Models: ai/llama3.2, ai/qwen2.5-coder, etc.
# - Enable: docker desktop enable model-runner --tcp 12434
# - Pull model: docker model pull ai/llama3.2
# - No authentication required
#
# Cross-platform note:
# - macOS/Linux: DMR_HOST=localhost (default)
# - Windows: DMR_HOST=host.docker.internal (to reach host from container)

# Reserved System Ports (never allocate these)
RESERVED_PORTS=22,25,53,80,110,143,443,993,995,5432,3306