Focus on in-memory authorization, graceful degradation, audit fidelity, and published overhead at real request rates. Those controls determine whether the gateway can support tool access in production without hiding risk behind vague platform claims. If a product cannot demonstrate them, the comparison is incomplete.
Why This Matters for Security Teams
When comparing mcp gateway options, the real issue is not feature count but whether the gateway can enforce access control at the moment a tool call is made. Model Context Protocol expands the number of possible interactions between an agent and downstream systems, so weak gateway design can turn a convenience layer into an authorization bypass. That is why in-memory authorization, audit fidelity, and request-time policy checks matter more than marketing claims about compatibility or scale. Current guidance in the OWASP Top 10 for Agentic Applications 2026 treats tool abuse, indirect prompt injection, and over-permissioned agent workflows as first-order risks, not edge cases.
This is also where NHI governance becomes practical. If an MCP gateway cannot show which identity was used, what context was evaluated, and whether the decision was enforced in memory rather than after the fact, then the control is mostly documentary. NHIMG’s Ultimate Guide to NHIs – Standards is useful here because MCP access is ultimately a non-human identity problem: the gateway is deciding what an autonomous workload may do, not just what a human operator can see. In practice, many security teams discover that gap only after a tool chain has already accessed data or executed actions that no one intended to permit.
How It Works in Practice
The strongest MCP gateways are evaluated on whether they can mediate each request with policy, identity, and telemetry intact. That starts with OWASP Agentic AI Top 10 style concerns: the gateway should not rely on static role assignments alone, because agents behave dynamically and may chain tools in ways that were never pre-approved. Instead, security teams should look for runtime authorization that can inspect task context, requested tool, data sensitivity, tenant, and risk signal before the call is forwarded.
In operational terms, the comparison should center on four controls:
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In-memory authorization: decisions are enforced during the session, not reconstructed later from logs.
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Graceful degradation: when policy services, identity providers, or telemetry sinks fail, the gateway should fail closed or reduce capability predictably.
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Audit fidelity: logs should preserve the exact request, decision path, identity, and downstream action.
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Published overhead at real request rates: security claims are not meaningful unless latency and throughput are shown under production-like load.
This is where implementation maturity matters. A gateway built around workload identity, short-lived tokens, and just-in-time credential handling is much easier to reason about than one that depends on long-lived shared secrets. NHIMG’s Analysis of Claude Code Security shows why agentic tooling needs stronger runtime controls than conventional app proxies, especially when tool use can expand quickly. These controls tend to break down when the gateway sits behind asynchronous queues or brokered tool execution, because authorization context is lost between the original request and the eventual action.
Common Variations and Edge Cases
Tighter gateway controls often increase latency, operational complexity, and integration effort, so organisations have to balance security depth against developer friction and uptime requirements. There is no universal standard for MCP gateway evaluation yet, but current best practice is evolving toward proving enforcement, not just configuration.
One common edge case is graceful degradation. Some products advertise resilience but silently fall back to permissive access when policy engines are unavailable. That is unacceptable for autonomous systems. Another is partial observability: a gateway may log the prompt and response but not the authorization context, making audits incomplete. A third is multi-tenant or multi-agent environments, where one agent’s context can bleed into another if session boundaries are weak.
NHIMG research on The State of MCP Server Security 2025 is a reminder that secrets exposure and weak tool scoping remain common in MCP deployments, so gateway review should include whether it actually reduces exposure rather than merely shifting it. In parallel, the AI Agents: The New Attack Surface report shows why auditability matters: once an agent moves beyond intended scope, the organisation needs a clear record of what was allowed, what was denied, and why. The practical test is simple: if the gateway cannot explain a decision at request time and preserve that evidence afterwards, it is not mature enough for production MCP traffic.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
OWASP Agentic AI Top 10, CSA MAESTRO and OWASP Non-Human Identity Top 10 address the attack and risk surface, while NIST AI RMF and NIST CSF 2.0 set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Agentic AI Top 10 | A2 | Addresses tool abuse and authorization failures in agentic workflows. |
| CSA MAESTRO | TRUST | Focuses on trust boundaries and runtime controls for agentic systems. |
| NIST AI RMF | Supports governance of autonomous AI behavior and accountability. | |
| OWASP Non-Human Identity Top 10 | NHI-03 | Gateway comparisons depend on credential handling and exposure risk. |
| NIST CSF 2.0 | PR.AC-4 | Least-privilege access management is central to gateway authorization. |
Map tool permissions to least-privilege controls and review them against real request paths.
Related resources from NHI Mgmt Group
- How should organizations prioritize security in their MCP implementations?
- What breaks when an MCP gateway creates a second access path outside existing IAM controls?
- Why do AI gateway and MCP gateway controls still leave security blind spots?
- Which controls matter most when AI agents use MCP or similar integrations?