AI Agent Gateways: the control plane for agentic AI
As enterprises move from single LLM calls to fleets of autonomous agents talking to models, tools, and each other, a new infrastructure layer has emerged to sit in the middle of it all. AI agent gateways route, secure, govern, and observe traffic across LLM providers, MCP servers, and agent-to-agent (A2A) communication — the same job an API gateway does for microservices, adapted for a world where the "APIs" are AI agents.
What an AI agent gateway actually does
Five capabilities show up again and again across the category, regardless of vendor.
Routing & Load Balancing
Directs requests across LLM providers and models, with automatic failover, retries, and semantic caching to control latency and cost.
Governance & Policy
Enforces access policies, budgets, and compliance rules across every agent, model, and tool call in the organization.
Security & Guardrails
Blocks prompt injection, PII leakage, and toxic content, and verifies agent identity before actions are executed.
Observability & Cost Control
Traces requests end to end, tracks spend per model or team, and surfaces usage analytics across the AI estate.
MCP & A2A Protocol Support
Applies the same control plane to Model Context Protocol tool calls and agent-to-agent traffic, not just LLM API calls.
The AI agent gateway directory
Open-source, cloud-provider, and enterprise-security offerings — search or browse below.
A unified AI security platform combining an AI Gateway control plane, agent identity verification, AI red teaming, runtime threat protection, and model vulnerability scanning across the full AI lifecycle.
Visit site →A routing-and-safety proxy layer offering sub-100ms PII detection, toxicity blocking, and prompt-injection defense alongside multi-provider routing, failover, semantic caching, and cost tracking.
Visit site →A control plane built into Kong AI Gateway for standardized security, governance, and observability across agent-to-agent (A2A) communication, with real-time RPC tracing and policy enforcement.
Visit site →An open-source gateway that unifies access to 140+ LLM providers and nearly 1,900 models behind a single OpenAI-compatible API, with spend tracking, budgets, and self-hosting support.
Visit site →Centralized governance, observability, and cost controls spanning agents, models, MCP servers, and tools within the Databricks Unity Catalog ecosystem.
Visit site →An open-source HTTP/gRPC gateway unifying traditional application traffic with AI-native protocols: LLM provider calls, MCP servers, and agent-to-agent traffic in a single data plane.
Visit site →An enterprise-grade, open-source AI gateway providing routing, governance, guardrails, and observability across multiple LLM and agent providers through one control plane.
Visit site →A Kubernetes-native API gateway built on Envoy Proxy and the Gateway API, paired with the agentgateway project for securing and governing inference, agentic, and MCP traffic.
Visit site →An open-source proxy between applications and LLMs offering model routing, load balancing, retries and fallback, token rate limiting, security, and observability.
Visit site →An open-source project built on Envoy Gateway for routing GenAI traffic to multiple providers, with multimodal support, MCP routing, and enterprise observability.
Visit site →An enterprise AI gateway for deploying, governing, and scaling LLMs and agents across on-prem, cloud, or hybrid environments, with unified routing, access control, and audit logging.
Visit site →An AI Agent Management platform unifying API management, event streaming, and agent governance, including identity management, access policies, and MCP tool authorization.
Visit site →Brings tool-level authentication, access control, per-tool rate limiting, and observability to remote MCP servers, alongside existing REST and GraphQL API management.
Visit site →A single control plane for both outbound LLM consumption and inbound MCP tool exposure, applying guardrails, usage monitoring, and cost optimization across AI traffic.
Visit site →A unified endpoint for accessing hundreds of AI models across providers with transparent, no-markup pricing, intelligent routing, automatic failover, and unified billing.
Visit site →Observability and control for AI applications at the edge, including analytics, logging, caching, rate limiting, and automatic model fallback.
Visit site →A model-agnostic AI Gateway offering one secure endpoint to access, route, and manage 200+ AI models, with built-in cost control and observability.
Visit site →Choosing a gateway
A few questions narrow the field quickly.
Open-source or managed?
LiteLLM, agentgateway, kgateway, Apache APISIX, and Envoy AI Gateway are open-source and self-hostable. Most cloud-provider and enterprise-security offerings are managed services.
Kubernetes-native?
kgateway and Envoy AI Gateway build directly on the Kubernetes Gateway API — a natural fit if your platform is already Envoy- or K8s-centric.
Do you need MCP support?
Tyk MCP Gateway, agentgateway, WSO2, and Gravitee explicitly govern MCP tool traffic — important once agents start calling internal tools, not just LLMs.
Security- or cost-first?
Prisma AIRS and Gravitee lead with agent identity and governance; Vercel, Cloudflare, and Nexos.ai lead with unified billing and multi-model cost control.