What Is Omni Gateway?

By Aston Whiteling, Senior Product Marketing Manager

Omni Gateway is an unified governance and visibility layer for API, MCP, LLM, and agent traffic, built as the next evolution of MuleSoft Flex Gateway. For teams already running Flex Gateway, this is an extension of the runtime they know, not a replacement for it. The same lightweight, high-performance engine now secures traffic from AI models and autonomous agents alongside the APIs it has always protected.

At its core, Omni Gateway operates as part of the agent control plane: the governance surface that specifies what autonomous agents are permitted to do and records what they actually do. Protocol support alone no longer sets a gateway apart, because most vendors can now proxy MCP or A2A traffic. The differentiator is federated governance across a mixed-vendor gateway estate, meaning one policy catalog applies consistent rules to traffic flowing through MuleSoft, Kong, Apigee, AWS, and Azure gateways without requiring a migration to any of them.

Two concerns sit inside that same governance surface: AI security and AI cost. Agents introduce new attack paths and new spend patterns, with token consumption chief among them, and both need to be controlled where the traffic actually flows. A standalone AI gateway can inspect LLM calls, but it adds one more policy silo to an estate that already has too many.

None of this abandons the product's roots. MuleSoft helped pioneer modern API management, and Omni Gateway remains one of the strongest API gateways on the market. What has changed is the company the gateway keeps: it now has to work alongside LLMs, MCP servers, agents, and the third-party gateways already deployed across the enterprise.

APIs are still a fundamental part of Omni Gateway.

The architecture splits into two components: a MuleSoft-hosted control plane and a distributed runtime that enforces policy wherever traffic flows. All communication between the two travels over connections secured with mTLS and HTTPS.

The control plane is where every human-facing governance action lives, making it the daily operational anchor for IT and platform teams. Its responsibilities include:

• Building and defining APIs in API Manager
• Adding and publishing policies to the policy catalog
• Deploying policies and configurations to the runtime
• Monitoring traffic, health, and compliance through API Manager
• Configuring and registering runtime instances through Runtime Manager

The runtime receives commands from the control plane and enforces them at the point of traffic, routing requests and protecting backend APIs according to the policies deployed to it. Every connection back to the control plane is secured with mTLS and HTTPS. That security-by-design detail matters in regulated industries, where the channel between governance and enforcement is itself subject to audit.

Choosing a deployment model is a decision about operational overhead versus infrastructure control, and it deserves deliberate consideration rather than a default answer.

A fully MuleSoft-hosted deployment running on CloudHub 2.0 or Runtime Fabric, with high availability, autoscaling, and automatic patching built in. Each runtime unit corresponds to a gateway instance. The headline benefit is point-and-click setup with no infrastructure code required.

Installed by the customer via Docker, Kubernetes, or supported Linux distributions, with each runtime unit running as a replica. Two modes are available. Connected Mode keeps the runtime continuously linked to the control plane. Local Mode runs mostly disconnected, using declarative configuration that fits naturally into CI/CD pipelines. One caveat worth stating plainly: Local Mode still checks in with the control plane for registration and usage metrics, so it should not be described as a fully air-gapped deployment.

API infrastructure was built for predictable, human-initiated request patterns. Autonomous agents break those assumptions, exposing gaps in token visibility, security policy coverage, and audit trails that most organizations have not yet closed. The timeline is compressed: 93% of IT leaders plan to introduce AI agents within the next two years, according to the 2026 Connectivity Benchmark Report from MuleSoft.

It would be easy to read this as an adoption problem, but the data points elsewhere. The same report finds that 95% of organizations cite integration as a hurdle to implementing AI effectively, which reframes the challenge as one of governance and connectivity rather than appetite. The industry's early response, standalone AI gateways deployed as point solutions, tends to deepen the fragmentation instead of resolving it. Each new gateway becomes another policy catalog to maintain, another audit surface to reconcile, and another seam through which an agent's behavior can slip unobserved.

Most organizations are extending governance from an imperfect starting point. In the 2026 Connectivity Benchmark Report, 87% of IT leaders agree that API management within their organization could be improved. Applying an inconsistent governance model to a new class of AI consumers compounds that debt, which is why federated enforcement across the whole estate matters more than any single capability.

• Federated policy enforcement. Policies are enforced across MuleSoft, Kong, Apigee, AWS, and Azure gateways from a single catalog, with no vendor migration required. Federation matters because governance gaps form at the seams between gateways, where inconsistent policies create the openings that agents and attackers find first. Enforcing from one catalog closes those seams without disturbing the infrastructure underneath.
• API-to-MCP conversion. Existing OpenAPI endpoints become governed MCP tools with authentication inherited from the source API. In practice, this turns years of API investment into an agent-ready tool library without rebuilding anything, giving MCP support real operational teeth rather than treating it as a checkbox.
• Token management and LLM routing. Consumption is tracked in real time across LLM calls, and routing between providers is governed centrally rather than hardcoded into each application.
• End-to-end monitoring and auditing. Correlation IDs follow a request across API calls, tool invocations, and agent delegations, so a single trace tells the full story of a transaction.
• Identity propagation and compliance. Identity context carries through agent-to-agent and agent-to-tool interactions, preserving the answer to "who did this, on whose behalf" even when the acting party is software several delegations removed from the original user.
• Cost optimization. A unified governance surface gives enterprises visibility into AI spend, enforces gateway-level budget caps, and automatically reduces token waste at the protocol level, all without requiring changes to existing agent code. For finance and platform teams alike, this is the difference between an AI program that can be budgeted and one that can only be reconciled after the fact.

Support for MCP and A2A alongside traditional API protocols is what separates an agent-ready gateway from a conventional one. Omni Gateway secures:

• HTTP
• WebSocket (no SLA tiers)
• SOAP
• gRPC
• GraphQL
• OAS3 REST
• MCP
• A2A

A useful way to think about agent governance is as four layers: Intent, Reasoning, Constraints, and Outcomes. Intent covers what an agent is designed to accomplish, Reasoning covers how it decides, Constraints cover what it is allowed to do, and Outcomes cover what it actually did.

Omni Gateway governs Constraints and Outcomes. It enforces the policies that bound agent behavior at runtime and produces the audit trail of what occurred. It does not govern Intent or Reasoning, which live upstream in agent definitions and orchestration platforms. Gateways are necessary for agent governance, but they are not sufficient on their own – any vendor claiming otherwise is overreaching.

The urgency of getting Constraints and Outcomes right is already visible in adoption numbers. Per the 2026 Connectivity Benchmark Report, 40% of IT leaders say they have already introduced AI agents, which means governance is chasing deployment in a large share of enterprises rather than preceding it.

Standalone AI gateways such as Kong AI Gateway and Cloudflare AI Gateway handle LLM traffic competently, but they arrive as net-new infrastructure. Omni Gateway's advantage is its installed API-platform base: organizations already governing APIs through MuleSoft gain AI governance in the same catalog, with no second policy store to maintain alongside existing tooling.

Incumbent API gateways such as Apigee, AWS API Gateway, and Azure API Management do not need to go anywhere. Federation is the new frontier, rather than migration. These gateways stay in place and continue serving traffic while Omni Gateway sits above them, applying consistent policy across the whole estate.

Hyperscaler agent control planes like AWS Bedrock AgentCore, Google Vertex AI Agent Builder, and Azure AI Foundry work well inside their own clouds. If everything you run lives in one of them, the native tooling may be all the governance you need. Most enterprises are not in that position. Agents end up spread across clouds, on-prem systems, and SaaS platforms, and each hyperscaler's tooling stops at its own boundary. Governing that kind of estate takes something that sits above all of them, which is where Omni Gateway operates.

It is also worth distinguishing Omni Gateway from MuleSoftMuleSoft Agent Fabric within MuleSoft's own portfolio. Agent Fabric is the agentic control plane where enterprises build, run, and orchestrate agents. Omni Gateway governs what is already running, whatever built it and wherever it lives. Omni Gateway is the governance component within that control plane.

The organizations that will run agents well are the ones that establish governance before deployment accelerates, rather than retrofitting it after incidents force the question. The strategic choice is between extending existing API governance discipline to cover AI assets or building a parallel stack that duplicates policy, identity, and observability for a second time.

For teams already running MuleSoft infrastructure, Omni Gateway is that extension. Details on availability and rollout are covered in the Omni Gateway announcement.