Unified AI traffic control
Govern LLM, MCP, and agent-to-agent traffic through a single gateway so API and AI traffic can be managed together.
Kong AI Gateway
RevendiquerKong AI Gateway centralizes governance for LLM, MCP, and agent-to-agent traffic with security, observability, routing, and cost controls.
Overview
Kong AI Gateway is a gateway for governing AI traffic across large language models, MCP resources, and agent-to-agent workflows. The product pages describe it as part of Kong’s broader AI connectivity platform, where API traffic, AI traffic, and real-time data are managed from one platform.
Its core job is to centralize security, routing, observability, and cost control for AI requests. The source highlights capabilities such as semantic caching, token-based rate limiting, prompt and PII protections, quota management, and telemetry for AI usage and spend.
Core capabilities
Layered security and policy enforcement
Apply PII sanitization, semantic prompt guards, access control, routing, and load balancing to AI requests.
AI observability and telemetry
Track token usage, AI consumption, tool usage, latency, errors, and cost with AI observability and metrics.
Cost and quota controls
Use semantic caching, token-based rate limiting, and quota management to control consumption and reduce unnecessary spend.
MCP governance
Generate and govern MCP servers and proxies, including auth for MCP access and context optimization.
Agent-to-agent governance
Manage multi-agent traffic with centralized AuthN/Z, auditability, and detailed telemetry on A2A calls.
Practical use cases
Control LLM access across teams
Centralize governance for applications and agents that call multiple LLMs, so access, routing, and usage policies are enforced in one place.
Operationalize MCP workflows
Put MCP-backed agent workflows into production with server generation, auth enforcement, and context optimization.
Govern multi-agent traffic
Track and manage agent-to-agent communication with telemetry, auditability, and centralized authorization for multi-agent systems.
Manage token usage and cost
Reduce AI spend by applying semantic caching, rate limits, quotas, and cost analytics to token-heavy workloads.
Protect sensitive AI traffic
Apply PII sanitization, prompt guards, and observability to AI requests that handle sensitive or regulated data.
Pros and Cons
Pros
- Consolidates LLM, MCP, and agent-to-agent governance into one gateway.
- Includes security controls such as PII sanitization, access control, and semantic prompt guards.
- Adds cost-management features like semantic caching, token-based rate limiting, and quotas.
- Provides AI-specific observability with token-level tracking and real-time cost analytics.
- Fits into Kong’s wider platform that also covers APIs, events, and developer workflows.
Cons
- The pricing page shows some AI Gateway capabilities only as paid plugins or enterprise plugins, so not every capability is included in the base trial or lower-tier packaging.
- The source pages do not provide a full public inventory of supported models, deployment environments, or external integrations.
FAQ
What does Kong AI Gateway do?
Kong AI Gateway governs LLM, MCP, and agent-to-agent traffic through a single gateway. The source pages describe centralized access control, routing, observability, token controls, semantic caching, and guardrails for AI traffic.
Is there a free trial or paid plan?
The pricing page shows a free trial for Kong Konnect, a Plus plan billed per Gateway per month, and an Enterprise plan with custom annual pricing. AI Gateway capabilities such as paid plugins are included in Plus and Enterprise packaging details shown on the pricing page.
Who is Kong AI Gateway for?
The product pages describe AI traffic governance for developers and platform teams working with LLMs, MCP resources, and multi-agent systems. Kong positions the gateway for production AI infrastructure rather than consumer chat use.
What kinds of AI workflows does it support?
The source highlights centralized security, routing, observability, quota management, and cost controls. It also describes support for LLMs, MCP servers, and A2A traffic, but does not provide a complete public list of every supported model or deployment option on these pages.
Quick Facts
- Category
- AI gateway / API management
- Platform
- Kong Konnect platform
- Primary users
- Platform engineering, API teams, and AI application teams
- Domain
- konghq.com
- Pricing signal
- Free trial available; Plus and Enterprise packaging listed
Alternatives à Kong AI Gateway
Orca
Orca is an Agent Development Environment for shipping with coding agents, running multiple CLI agents in parallel across isolated worktrees, with desktop and mobile workflows.
AI Magicx
AI Magicx is a unified AI workspace for chat, image, video, voice, music, email and developer tasks, helping teams and creators manage multiple models in one place.
Paper
Paper is a design tool that connects canvas, code, and AI agents so teams can create, share, and ship work in one workflow. Includes desktop app and MCP access.
blop
blop is a QA agent that writes browser tests as code in your repo, runs them in CI, clusters repeated failures, and can open PRs to fix broken tests.
RLAMA
RLAMA is a local AI platform for building RAG systems and intelligent agents on macOS, Linux, and Windows, with HTTP API support.
Kastra
Kastra authorization infrastructure for AI systems checks prompts, tool calls, shell commands, API requests, and browser actions before execution.