This topic compares Model Context Protocol (MCP) tunnels, gateways and supporting solutions used to deliver, secure and manage context for AI assistants and API gateways. MCP tunnels provide the secure transport channel for context; MCP gateways act as enforcement, routing and observability points that gate model access and apply policies. As organizations in 2026 increasingly rely on AI agents and distributed API gateways, policy control, cost visibility and operational observability for MCP traffic have become routine requirements. Key components described here include: Archestra.AI — an open-source, enterprise-ready centralized MCP platform for managing MCP servers, registry, orchestrator, security, cost monitoring and observability; Kong Konnect — an MCP server exposing Kong API Gateway analytics and configuration for assistant-driven queries and inspections; OPNSense MCP — an MCP server for direct OPNsense firewall management and troubleshooting; SafeLine — a self-hosted Web Application Firewall (reverse-proxy WAF) for filtering and blocking malicious HTTP/S traffic; and sslmon — an MCP server offering domain registration data and SSL certificate monitoring. Together these categories address operational needs: centralized governance (Archestra.AI), gateway analytics and policy interrogation (Kong Konnect), firewall control and diagnostics (OPNSense MCP), application-layer protection (SafeLine), and certificate/registration hygiene (sslmon). The landscape reflects two clear trends: a shift toward self-hosted, observable MCP infrastructures to meet security/compliance needs, and tighter integration between model-context channels and existing network/security tooling to reduce attack surface and downtime. This comparison helps teams choose the right mix of tunnel, gateway and adjunct services to enforce policy, maintain uptime and keep context transport auditable and secure.