Tetrate Agent Router vs. Kong AI Gateway: AI-Native vs. API Management Heritage
Tetrate Agent Router vs. Kong AI Gateway: AI-Native vs. API Management Heritage
Last updated: June 2026
TL;DR
Kong AI Gateway is a serious, mature player — it has shipped first-class MCP support (3.12), A2A agent traffic governance (3.14), and a public benchmark methodology. It is the natural choice for organizations already standardized on Kong. Tetrate Agent Router is built AI-native on the Envoy AI Gateway data plane by the team that created it — the architectural question is plugin-extended API gateway vs. purpose-built AI gateway.
What each product is for
Kong AI Gateway extends the Kong platform — historically a proven API gateway (nginx/Lua) — into AI, MCP, and now agent-to-agent (A2A) traffic management. It shipped MCP support in 3.12, and in April 2026 launched Agent Gateway in 3.14 claiming unified governance of LLM, MCP, and A2A traffic. It is a credible, fast-moving enterprise choice for organizations already standardized on Kong.
Tetrate Agent Router starts from a purpose-built AI gateway in the Envoy project. Tetrate co-created and maintains Envoy AI Gateway, with Bloomberg, and productizes it with managed operations, authenticated identity, per-team cost attribution, MCP tool governance, and compliance-grade audit.
The key question is architecture: extending a battle-hardened API gateway into AI via plugins vs. starting from an AI gateway built for that purpose on a different data plane.
Head-to-head comparison
| Kong AI Gateway | Tetrate Agent Router | |
|---|---|---|
| Heritage | API management (nginx / Lua + plugins) | AI-native (Envoy AI Gateway) |
| AI capabilities | Plugin-based; plugin ecosystem is extensive | Native (MCP, guardrails, attribution) |
| Deployment | Self-host + Konnect (managed) | Tetrate-managed control plane + data planes in VPC/on-prem/per-region/edge (not fully customer-hosted) |
| MCP / tool governance | Shipped — MCP Proxy plugin (3.12), OAuth 2.1, token rate limiting, Prometheus metrics, A2A in 3.14 | Native: curated tool catalog, MCP profiles, OAuth + API-key auth |
| Cost attribution | Via Kong analytics | Per-person / team / agent / project; showback + chargeback |
| Runtime guardrails | AI plugins (PII redaction, guardrails) | Built-in PII redaction, policy enforcement, behavior supervision |
| Audit / compliance | Enterprise tier | Immutable audit logs; EU AI Act-grade |
| Envoy AI Gateway lineage | No (competing proxy stack) | Co-creator and maintainer |
One control plane, distributed data planes
Kong’s deployment model is self-host (plus Konnect for managed). Tetrate Agent Router Enterprise runs a fundamentally different topology: one Tetrate-managed control plane governing distributed data planes deployed wherever your agents run — Tetrate-hosted, inside your own AWS/Azure/GCP VPC, on-premises, at the edge, or per-region with localized model catalogs and guardrails. Each data plane can enforce region-specific compliance policies, model catalogs, and guardrails, all from a single governed control point without duplicating logic in each application.
For enterprises already running Envoy Gateway and Istio for ingress and service mesh, this extends the same distributed architecture they already operate to AI traffic — same data plane, same operational model, same team behind it. Kong’s control plane (Konnect) governs Kong Gateway instances; it does not extend to Envoy-native AI workloads.
A note on performance benchmarks
Kong publishes a transparent, open-source benchmark methodology — commendably, the test suite is public and reproducible. The published figures compare Kong against Portkey and LiteLLM using mock LLM backends under default gateway configurations, which Kong itself acknowledges: their own AI Gateway docs state to “benchmark with your real workload and avoid relying on synthetic or idealized figures.”
In other words, Kong’s headline numbers are a useful baseline for proxy overhead, not a production comparison under governance load. The same caveat applies to Tetrate’s benchmarks. What matters is performance with your policies, plugins, and auth enabled. Both vendors publish open methodologies — run both under your actual policy profile before deciding.
Choose Kong AI Gateway when
- Your organization has already standardized on Kong and you want a single control plane for API, LLM, MCP, and A2A traffic.
- You need a mature plugin ecosystem with years of enterprise hardening.
- Your AI and agent traffic is a natural extension of existing API workloads.
Choose Tetrate Agent Router when
- You are building AI/agent infrastructure and want MCP, guardrails, and cost attribution native to the data plane — not added as plugins.
- You want your gateway operated by the team that built and maintains Envoy AI Gateway.
- You need compliance-grade audit, data-residency control, and cross-team governance for regulated AI deployment.
Now Available
MCP Catalog with verified first-party servers, profile-based configuration, and OpenInference observability are now generally available in Tetrate Agent Router Service. Start building production AI agents today with $5 free credit.
Frequently asked questions
Can I run Tetrate Agent Router alongside Kong? Yes — a common architecture uses Kong for existing API traffic and Tetrate Agent Router as a dedicated AI/agent gateway. They address different layers and are not mutually exclusive.
Is Kong’s performance advantage real in production? Kong’s published benchmark uses mock LLM backends under default configurations — a controlled proxy-overhead measurement, not a governance-loaded production test. Kong’s own docs explicitly recommend against relying on synthetic figures. Run both under your actual policy and plugin load before drawing conclusions.
Does Kong support MCP natively? Yes — Kong shipped first-class MCP support in Gateway 3.12 (AI MCP Proxy plugin, OAuth 2.1, token rate limiting, Prometheus metrics) and added A2A agent traffic governance in 3.14. If you are already on Kong, this is a credible MCP path. Tetrate’s MCP gateway is native to the data plane rather than plugin-based, and runs wherever your Agent Router data plane runs (including on-premises data planes under a Tetrate-managed control plane).
Compare other gateways: vs. Portkey · vs. Bifrost · vs. Cloudflare AI Gateway · vs. Envoy AI Gateway (OSS) · vs. LiteLLM
See the full 2026 enterprise AI gateway comparison.
MCP Catalog with verified first-party servers, profile-based configuration, and OpenInference observability are now generally available in Tetrate Agent Router Service . Start building production AI agents today.
