Give your teams AI access. Keep every call accountable.
One gateway in front of the MCP servers and models you approve. Teams sign in with your IdP, budgets keep spend in bounds, and every tool call is audited per user — on the same policy engine that runs your APIs.
Saying yes to AI shouldn't mean losing track of it.
Your teams want Claude, Cursor, and ChatGPT wired into real systems, and your apps are calling models in production. The job isn't to slow any of that down — it's to give it a front door you control.
Approve once, publish one gateway
Vet an MCP server or model provider once, put it behind the gateway, and every team connects to the same governed endpoint. Saying yes gets faster, not riskier.
Budgets, not surprises
Per-team dollar budgets and spend caps on LLM traffic. Teams experiment freely inside limits you set — and the bill never outruns the plan.
Every call has a name on it
Every tool call and completion is attributed to the person behind the agent. When someone asks who did what, you answer from a dashboard, not a shrug.
One front door for AI, in three steps
Put the gateway in front
Add the MCP servers you approve — Linear, GitHub, Stripe, or your own internal ones — as routes on one gateway deployment, and route LLM traffic through the AI Gateway alongside them.
Teams sign in with your IdP
Claude, Cursor, and ChatGPT connect through standard MCP OAuth backed by Okta, Microsoft Entra ID, Auth0, or any OIDC provider. Any client, any IdP, any auth method — and no shared keys in desktop apps.
Policies do the governing
Per-tool allow-lists, rate limits, dollar budgets, and audit logging run on every call — written once, enforced at the edge, versioned in your repo like the rest of your gateway config.
The MCP your teams use and the models your apps call
Agent tool calls and LLM completions run through the same gateway and the same policy pipeline — one place to set the rules, one place to see what happened.
Each gateway runs as its own project. MCP Server Support is built directly into the API Gateway — no extra deployment, no duplicate config.
The MCP servers your teams use
Front approved MCP servers from one deployment — one route per upstream. The gateway brokers credentials for you: per-user OAuth tokens encrypted at rest with automatic refresh, or a shared connection where a service account fits better. Curate exactly which tools each route exposes.
Explore MCP GatewayThe models your apps call
Route traffic across model providers in config, not code, with per-team dollar budgets and spend caps attached. Compose prompt-injection detection and secret masking as policies on the same pipeline.
Explore AI GatewayPer-tool access. Per-user answers.
Per-tool access, enforced at the gateway
Capability filtering allow-lists the tools, prompts, and resources each route exposes — and blocks hidden tools even when a client invokes them by name. Go finer-grained with OpenFGA, AuthZEN, or Okta FGA integrations, or custom TypeScript authorization.
Audited per user, not per key
Every tool call carries the user's identity, client, capability, outcome, and latency. Slice it by team or upstream in Zuplo's analytics, or forward it to Datadog, Splunk, or New Relic next to the rest of your telemetry.
Works with the identity provider you already run
Teams sign in with the accounts they already have. Eleven first-class identity provider integrations, plus generic OIDC for everything else.
Frequently Asked Questions
Common questions from platform and IT teams governing AI and agent access.
Give your teams AI access today
Put one governed gateway in front of the MCP servers and models you approve. The MCP Gateway and AI Gateway are included in every plan.