Lunar.dev MCP Gateway (MCPX) vs Raven Runtime AI Agents: Side-by-Side Comparison (2026)

Lunar.dev MCP Gateway (MCPX)

Security teams deploying Claude or other agentic AI systems will find real value in MCPX's per-agent tool restrictions and immutable audit logs that actually capture prompt payloads and attribution, not just API calls. The role-based access control with on-behalf-of tracking addresses the specific governance gap that makes AI agents harder to audit than traditional service accounts. This tool prioritizes Govern and Detect over Respond, which works if your security model treats agent behavior as inherently less trustworthy than human access. Skip MCPX if you're looking for a lightweight proxy; the MCP Risk Score Engine is beta and Lunar.dev's 15-person team means you're betting on a startup's ability to track an evolving threat surface faster than vendors with security divisions.

Raven Runtime AI Agents

Mid-market and enterprise security teams deploying AI agents in production need visibility into shadow AI that code review won't catch, and Raven Runtime AI Agents discovers and monitors agents without requiring registration or SDK changes across Java, Node.js, Python, and Go environments. The passive instrumentation model means you get real-time agent behavior tracking and policy-based blocking without the overhead that kills production workloads. Skip this if you're looking for agent governance at the development or pre-deployment stage; Raven is explicitly a runtime control tool, not a supply chain solution.