# Govern all AI traffic. Do it with one gateway.
Govern LLM, MCP, and agent-to-agent (A2A) traffic with the same Kong AI Gateway.
## Fragmented API & AI traffic
## APIs. LLMs. Agents. One platform for API and AI traffic.
## Build agents faster. Optimize token spend. Mitigate AI risks.
Govern how developers, apps, and agents consume LLMs. Control everything from access, to data leakage, to token usage.
Generate MCP servers and govern how agents discover and consume them. Optimize context and implement critical auth solutions for production-ready MCP.
Roll out an agent gateway to fully govern *all *multi-agent traffic, with auth, observability, and auditability baked-in.
Don’t settle for fragmented AI gateway solutions, and don’t settle for solutions that aren’t hardened for enterprise usage. Unify all AI traffic in one secure, resilient platform.
## Watch Kong AI Gateway in action
## Route and manage AI traffic at scale
[Watch the Video](#)Watch the Video
## Secure your AI with layered guardrails
[Watch the Video](#)Watch the Video
## Cut AI costs without cutting corners
[Watch the Video](#)Watch the Video## The agentic era demands a new kind of agentic infrastructure
Govern all generative AI and agentic AI traffic with a single gateway for LLM, MCP, and A2A connectivity.
## Enforce advanced LLM policies
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Stop data leakage and avoid compliance nightmares with PII sanitization.
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Make LLM traffic more efficient with semantic caching, routing, and load balancing.
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Protect resources and ensure compliance with semantic prompt guards, access control, and more.
## Make MCP-powered agents a production reality
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Automatically generate intelligent MCP tools and servers on top of Kong-managed APIs.
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Enforce auth for MCP server access control.
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Optimize token spend through MCP context optimization.
## Govern complex, multi-agent systems
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Observe all A2A traffic and capture A2A-specific metrics.
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Capture detailed telemetry on every A2A call, including payloads, latency, token usage, and errors.
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Enforce centralized AuthN/Z for all A2A traffic.
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Audit and track every A2A RPC call with information around caller identity, capabilities invoked, and more.
## Because AI traffic is more than just AI-native traffic
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Govern how agents consume context from your API and event data estate.
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Observe and govern the application, intelligence, and context layers – all from one platform.
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Deliver enterprise data, events, APIs and agent-ready context.
## Advanced LLM and token quota management
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Set up user, model, and time-bound quotas around LLM consumption and token spend.
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Enforce quotes at the gateway level.
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Build showback and chargeback for LLM, agent, and MCP usage across the enterprise.
## L7 observability on AI traffic for cost monitoring and tuning
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Track AI consumption, tool usage, token spend, and more.
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Optimize AI usage and cost with predictive consumption models.
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Debug AI exposure via logging, tracing, and more.
## Ensure every LLM use case is covered
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Use Kong’s unified API interface to work with multiple different AI providers at the flip of a switch.
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Seamlessly switch between AI providers to unlock new use cases and ensure high availability in the event of downtime.
## Kong AI Gateway FAQs
Questions teams ask before AI hits production
What is an AI gateway, and what does Kong AI Gateway do?
An AI gateway provides a central place to route, secure, and manage AI traffic. Kong AI Gateway governs large language model (LLM), MCP, and agent-to-agent (A2A) traffic, helping teams control access, manage token usage, and monitor AI consumption.
Can Kong AI Gateway work with multiple AI providers?
Yes. Kong AI Gateway provides a unified API interface for working with multiple AI providers and switching between them. It also supports routing and load balancing to make LLM traffic more efficient, while provider switching helps maintain availability during downtime.
How does Kong AI Gateway help secure AI traffic?
Kong AI Gateway provides layered controls, including access control, personally identifiable information (PII) sanitization, and prompt and content guardrails. These capabilities help reduce data leakage risks and enforce policies for LLM consumption. It also supports authentication for MCP server access and centralized authentication and authorization for A2A traffic.
How can Kong AI Gateway help control AI costs?
Kong AI Gateway supports semantic caching and MCP context optimization to make AI usage more efficient. You can set user, model, and time-bound quotas for LLM consumption and token spend, then enforce those quotas at the gateway. Usage tracking also supports showback and chargeback across LLM, agent, and MCP usage.
Does Kong AI Gateway support MCP governance?
Yes. Kong AI Gateway can automatically generate MCP tools and servers on top of Kong-managed APIs and govern how agents discover and consume them. It also provides authentication for MCP server access and context optimization to help manage token spend.
Can Kong AI Gateway govern communication between AI agents?
Yes. Kong AI Gateway governs agent-to-agent traffic with centralized authentication and authorization, observability, and auditability. Teams can capture call details such as payloads, latency, token usage, and errors, and audit calls using information about caller identity and the capabilities invoked.
What visibility does Kong AI Gateway provide into AI usage?
Kong AI Gateway tracks AI consumption, tool usage, and token spend to support cost monitoring and tuning. Logging and tracing help teams debug AI traffic, while A2A-specific telemetry provides visibility into agent calls, latency, and errors.
Can Kong help govern the APIs and data that AI agents use?
Yes. Kong’s platform extends governance beyond AI-native traffic to how agents consume context from APIs and event data. Through Kong Context Mesh, teams can observe and govern the application, intelligence, and context layers from one platform and deliver enterprise data, events, APIs, and agent-ready context.