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An LLM gateway routes model requests; an agentic gateway governs the wider paths an AI system uses to discover and invoke tools, reach HTTP services, and communicate with other agents. Build it as a policy-enforcing data plane backed by a separate configuration and operations layer. The gateway can enforce controls only on traffic that actually passes through it, so begin by mapping every allowed path and closing or monitoring alternate routes.
This guide uses a vendor-neutral architecture, not a particular programming language or hosting platform. The design assumes a gateway that can proxy model-provider requests, expose or route MCP tools, and route HTTP or agent traffic. Those are separate capabilities, not a universal definition: decide which you will support and document the limits of each.
What changes when a model proxy becomes an agentic gateway?
A basic LLM gateway sits between an application and model providers. It can authenticate the application, choose a provider or model, apply request policies, and record operational metadata. An agentic system adds more kinds of traffic: an agent may discover tools, invoke an MCP server, call an HTTP service, or hand work to another agent. Each path has its own protocol, identity, authorization, and failure behavior.
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- Model routing selects and forwards inference requests to model providers.
- Tool routing makes tools discoverable and controls invocation of MCP or other tool targets.
- Service and agent routing forwards HTTP or agent-to-agent traffic, potentially without translating its protocol.
Do not infer that model-provider selection grants permission to use tools. Model routing and tool authorization are different responsibilities.
Start with the request paths and trust boundaries
Draw the actual routes before building policy. For each caller, identify whether it can reach the gateway, which targets it can reach, and which credentials are used on each leg. A gateway cannot enforce a policy on a direct connection that bypasses it.
- List callers: applications, users, agents, and internal services that can submit requests.
- List targets: model providers, MCP servers, HTTP services, and agent endpoints.
- Map each allowed path: record the protocol, caller identity, target identity, and data that crosses each boundary.
- Decide what must traverse the gateway: route those paths through it and restrict or monitor alternate access at the network or service layer.
- Define policy ownership: decide which rules are enforced centrally and which remain with the target service.
Keep the inbound caller identity distinct from outbound credentials. A valid gateway key can identify a client; it should not become blanket permission to invoke every upstream or tool. Kong documents separate consumer authentication and provider credentials. AWS documents inbound authorization and target credentials, while NVIDIA’s DSX Agent Gateway architecture describes tenant identity derived from verified JWT claims.
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Build the gateway as a data plane plus a control plane
Data plane: enforce policy on the live request
The data plane receives traffic, authenticates the caller, authorizes the requested route, applies limits, forwards the request, handles timeouts and eligible retries, and emits telemetry. Keep the path from authentication to forwarding explicit so a request cannot reach an upstream before its access checks finish.
Control plane: validate and distribute configuration
Store provider and target definitions, route rules, caller or tenant access, and references to secrets in a configuration layer. Validate changes before distributing them to request-processing nodes; reject invalid or incomplete target definitions rather than letting each node interpret them differently. Define how nodes receive updates and what happens if they lose contact with the control plane.
Separate control and request paths where practical. Kong’s documented hybrid arrangement keeps user data on self-managed data-plane nodes and says its managed control plane stays out of the data path by default. That is a vendor-specific deployment example, not a requirement for every build.
Keep secrets out of ordinary configuration and logs
Store references to outbound credentials in configuration and retrieve the secret through the deployment’s secret-management mechanism. Associate each credential with a specific upstream or target, support rotation, and avoid returning it to callers or exposing it in error messages. The gateway’s inbound authentication material and a provider’s outbound API credential serve different purposes and should have separate scopes and lifecycles.
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Define routes by target type
Use an explicit target type in configuration rather than treating every upstream as an interchangeable URL. The type determines protocol handling, authorization checks, telemetry, timeouts, and which transformations are allowed.
| Target type | Gateway responsibility | Design decision |
|---|---|---|
| Model provider | Map a stable gateway-facing model request to a provider endpoint and its credential; apply model-routing policy and capture usage outcomes. | Choose supported providers and request/response behavior. Define timeout, bounded retry, and failover rules per route. |
| MCP server or tool source | Proxy a server, aggregate capabilities from sources, or adapt an API into MCP tools, then enforce access to the resulting tools. | Choose and document which integration pattern is supported. They have different compatibility and operational consequences. |
| HTTP service | Authorize and forward HTTP traffic, with translation only if the gateway explicitly provides it. | Decide which HTTP methods, destinations, and credentials are allowed; do not imply protocol conversion where there is none. |
| Agent endpoint | Route agent-to-agent traffic under its protocol and authorization rules. | Define destination allowlists, identity expectations, and whether requests are session-bound. |
Kong documents patterns including proxying MCP servers, aggregating sources, and adapting REST APIs into MCP tools; HTTP and A2A traffic may instead pass through. AWS likewise distinguishes MCP targets from HTTP targets, which pass through without protocol translation, and inference targets routed by requested model. Treat these as examples of distinct integration choices, not interchangeable gateway behavior.
Implement the request lifecycle in a fixed order
- Receive and classify: identify the route and target type from gateway configuration, not from an untrusted caller claim alone.
- Authenticate inbound: validate the caller using the chosen mechanism, then attach a verified identity and relevant tenant context to the request.
- Authorize the operation: check whether that identity may use this model, tool, HTTP destination, or agent route. Apply the narrowest useful scope, such as tenant plus target or tool.
- Apply limits and validation: enforce request-size, rate, and route-specific input rules before forwarding. Return a clear denial or validation error without contacting the target.
- Resolve the target and credential: select the configured endpoint and retrieve only its required outbound credential.
- Forward under bounded transport rules: use explicit deadlines and retry rules appropriate to the operation. Do not retry a side-effecting tool call blindly.
- Record outcome metadata: capture route, status, latency, and applicable usage or cost information, while following the payload-logging policy.
This order creates a useful audit trail: the system can distinguish caller authentication failures, authorization denials, gateway routing errors, and upstream failures.
Make routing, retries, and failover deliberate
For model traffic, a stable gateway-facing interface can map a requested model to a provider endpoint and credential. Specify routing rules explicitly: which providers are eligible, how a route is selected, what happens when a provider is unhealthy, and whether a fallback changes model behavior. A unified endpoint can simplify clients, but it does not make providers’ capabilities or outputs identical.
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Kong documents load-balancing strategies, retries, and failover for its model routing, and its architecture page gives product-specific configuration examples such as five default retries and a 30-second keepalive. Those are Kong implementation values, not general recommendations or performance findings. Set and test your own values against your upstreams and request semantics.
Treat identity, authorization, and rate limits as separate controls
- Inbound authentication answers who is calling the gateway.
- Authorization answers which target or operation that verified identity may use.
- Outbound credentials let the gateway authenticate to a provider or service; they do not establish the caller’s rights.
- Rate limits constrain request volume and should be scoped to an identity or tenant where appropriate, as well as to the resource being protected.
For MCP, authorization should reach the level needed to control tool access, not stop at permission to connect to a server. For HTTP and agent targets, constrain permitted destinations and operations rather than allowing arbitrary forwarding. NVIDIA’s DSX Agent Gateway architecture documents JWT verification, tenant-aware rate limiting, and target authorization as parts of its design; those are product capabilities, not requirements imposed on every gateway.
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Choose session and discovery behavior explicitly
Decide whether the gateway handles independent stateless requests or preserves session context. If a protocol or target requires a stable session, document how the gateway maintains affinity and what happens when the selected target becomes unavailable. Do not route a session-bound exchange as though every request were interchangeable.
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Make observability useful without logging everything
Record enough metadata to answer operational questions: which route was selected, whether authentication and authorization passed, the target outcome, latency, and model usage or cost where available. Correlate events with a request identifier, but avoid putting secrets or unnecessary personal data into logs.
Payload logging is a separate decision. It can help diagnose malformed requests or tool failures, but model prompts and tool arguments may contain sensitive data. Make payload capture opt-in or otherwise explicitly governed, restrict access and retention, and make redaction part of the design. Kong documents opt-in payload logging and default telemetry focused on metadata rather than request and response bodies; that is one implementation’s choice, not a universal default.
Test the boundaries and failure cases
Test each target type independently and then test mixed agent flows. A passing model-proxy test does not demonstrate that tool authorization or session routing is correct.
- Identity: invalid, expired, and valid credentials; tenant context that is missing or does not match the requested target.
- Authorization: a permitted model with a forbidden tool, a permitted tool with a forbidden target, and attempts to reach unconfigured destinations.
- Upstream behavior: slow responses, unavailable targets, malformed responses, and credential rotation.
- Retry safety: confirm that retries stop at the configured bound and that side-effecting operations are not duplicated.
- Sessions: verify target affinity where required and define behavior if the target or gateway node fails.
- Privacy: verify that payloads, credentials, and sensitive tool arguments are absent from ordinary telemetry unless explicitly allowed.
- Bypass paths: confirm that clients cannot silently use direct upstream connections when policy requires gateway mediation.
How established gateway examples differ
The following comparison summarizes capabilities described by the products’ own architecture or concept documentation. It is not a claim that the products are interchangeable or that every listed capability is available in every edition or deployment.
| Example | Deployment and traffic described | Integration and controls described | What to verify for a real deployment |
|---|---|---|---|
| Kong AI Gateway | Kong documents a hybrid control-plane/data-plane architecture and LLM, MCP, and A2A traffic. Its architecture page identifies AI Gateway 2.0 as the minimum version for the described entity model and says that model is hybrid-only. | Documentation describes model routing, policy entities, and opt-in payload logging. | Check the current product version, deployment options, and whether the documented entity model applies to the chosen setup. |
| Amazon Bedrock AgentCore Gateway | AWS documents a managed gateway with MCP, HTTP, and inference target categories. | MCP targets can aggregate capabilities; HTTP targets pass through without protocol translation; inference targets route by requested model. Documentation also describes inbound authorization and upstream target credentials. | Confirm current target support, authorization configuration, and credential behavior for the intended AWS deployment. |
| agentgateway | Project documentation describes an open-source HTTP/gRPC data plane for ordinary API and LLM, MCP, and A2A traffic. | Project documentation describes TLS, authorization, rate limiting, retries, and traffic policies. | Verify current project status, maturity, release behavior, and operational fit. The project’s documentation says it was donated to the Linux Foundation in 2025 and accepted as an Agentic AI Foundation project in 2026. |
| NVIDIA DSX Agent Gateway | NVIDIA’s architecture documentation describes an MCP routing layer integrated with Kubernetes gateway components. | It describes JWT verification, tenant-aware rate limiting, target authorization, MCP catalog and routing, sessions, and optional cross-shard bridging. | Check the current architecture and session behavior against the deployment. The documentation was last updated August 14, 2026. |
A practical build sequence
- Ship model proxying first: implement inbound identity, provider-specific outbound credentials, explicit routing, deadlines, and metadata telemetry.
- Add configuration validation: represent model and service targets with explicit types; validate credentials references and route permissions before activation.
- Add MCP deliberately: choose proxying, aggregation, or API adaptation, then add tool-level authorization and discovery behavior for that pattern.
- Add HTTP and agent routes: constrain destinations and define whether each route passes through or translates a protocol.
- Add operational controls: test bounded retries, failover, session affinity where required, payload-handling rules, and tenant-level limits.
- Prove mediation: verify that the application’s model, tool, and agent traffic follows the intended gateway paths and that alternate routes are controlled.
This sequence keeps the gateway’s scope understandable: each new traffic class brings its own protocol and security questions, rather than merely adding another upstream URL.
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