Per-tool authorization for AI agents

AI Agent Gateway sits between agents and the systems they act on.

An agent's tool call -- to Gmail, internal applications, databases, or third-party MCP servers -- is intercepted, checked against a per-user, per-tool permission map, and either forwarded and logged or denied. The agent never holds the credentials directly. Permissions can be granted, scoped, or revoked at any time without changing the agent.

See how it works
01   The gap

Agents are running in production. Nothing checks what they actually do.

Prompts shape what agents are asked. Agent frameworks define how they are built. MCP wires them to systems. None of those layers checks, at the moment of the call, whether the agent is allowed to do what it just decided to do.

[ 01 ]

Credential sprawl

Every agent-to-tool connection keeps its own API keys and service accounts. Credentials scatter across environments with no central control.

[ 02 ]

Invisible actions

An agent deletes a production record, sends a customer email, or surfaces PII in a response. Without an audit trail, nobody knows until the damage is done.

[ 03 ]

Unbounded access

Most frameworks give every agent access to every tool. There is no concept of least privilege. A sales agent can reach engineering databases.

02   How it works

Every agent action passes through AI Agent Gateway.

A single enforcement point between agents and enterprise systems. Deployed inside your infrastructure. No agent changes required.

Three-layer isometric stack: agents on top, AI Agent Gateway in the middle, gated downstream systems at the base
Request

The agent asks. We check. The system responds.

No framework rewrites. No new SDK. An agent configured for MCP, REST, or HTTPS points at AI Agent Gateway and inherits the entire enforcement model.

# agent calls a tool
POST /mcp/tools/call
{
  "tool": "gmail.send",
  "args": { ... },
  "token": "st_a1b2c3..."
}

# AI Agent Gateway enforces
→ scope check
→ guardrail check
→ audit log

200 { "status": "sent" }
5min
Deployment time
100%
Audit coverage
1:1
Instance per customer
0
Data egress
03   What it is not

Five adjacent tools, each doing real work. None of them check the AI agent request before it reaches the system.

Adjacent approach What it does What it does not
Prompt engineering Shapes what agents are asked to do. Cannot enforce what they are allowed to do.
Agent frameworks Define how agents are built. Do not define how agents are controlled in production.
API gateways Control network traffic. Have no awareness of agent intent, scope, or business context.
Observability Tells you what happened. Does not prevent what should not happen.
MCP Enables connection. Does not enforce control.
04   Who it is for

Built for the teams that actually own the outcome.

[ 01 ] ENGINEERING

Deploy in five minutes.

Inside your VPC or data centre. No agent changes. Point any MCP, REST, or HTTPS client at AI Agent Gateway and inherit the enforcement model.

[ 02 ] SECURITY

Audit every action.

Scoped permissions per user, per sub-token, per tool. Append-only audit trail with optimistic locking. No silent last-writer-wins.

[ 03 ] LEADERSHIP

Approve with confidence.

Before an agent takes an action that matters, the action is enforced against policy. What happened is knowable. What can happen is bounded.

AES-256Credential encryption at rest
Argon2Password hashing
TLS 1.3In-transit, production default
Self-hostOne instance per customer
05   Before and after

Replace scattered controls with one enforcement point.

Today

  • Credentials managed per integration
  • Audit trails built per application
  • Broad access, manually scoped
  • Usage reviewed at invoice time
  • Safety checks reimplemented per agent
  • Each team adopts AI independently

With AI Agent Gateway

  • Single token per user, sub-tokens per agent
  • Every action enforced and logged uniformly
  • Least privilege enforced on every agent request
  • Real-time cost attribution by team and model
  • Guardrails enforced at the gateway, not per app
  • Structured adoption with a central registry
06   Start

Deployed in your infrastructure in five minutes. No agent changes required.

AI Agent Gateway runs on your own server. You connect the agent to it the same way you'd connect to any other MCP server, then grant the user the specific tools they're allowed to use. We do not build agents. We do not host agents. We authorize what they do.