AI Governance

AI Agent Security

Govern every MCP / API call your AI agents make — authenticate with your existing IAM, enforce least-privilege access, meter usage, redact sensitive data, and route to the right model — all without changing agent code.

Overview

RequestRocket in the AI Stack

RequestRocket sits between your AI agents and the MCP / APIs they call. Every request passes through authentication, access control, rate limiting, and optional transforms before reaching the upstream — and every response is filtered, shaped, and logged before returning to the agent.

Consumers
Agents
Applications
Intelligence
Webhooks
Regional / Customer Deployments
Identity & Access Management
OktaMicrosoft EntraAuth0CognitoPing IdentityKeycloakJumpCloudFirebase AuthForgeRockCustom OIDC
Data Planeruntime proxy
Authentication
Rate Limiting
Authorization
Transformation
Handler
Filtering
Redaction
Payload Transform
3rd Party APIs
AI / ML
Payments
CRM
Comms
Data

The Problem

Why AI Agents Need Runtime Controls

AI agents make autonomous API calls — to LLMs, third-party services, internal tools, and data sources. But the credentials they carry are typically long-lived, over-scoped, and shared across agents. There is rarely per-agent identity, no usage governance, and no consistent audit trail.

Over-scoped credentials

Agents typically share a single MCP / API key or service account with full access to every endpoint. Compromising one agent compromises every system it can reach. There is no way to scope, rotate, or revoke access for a single agent without disrupting others.

No visibility or limits

Without metering or logging at the proxy layer, a runaway agent can exhaust API quotas, leak PII into context windows, or generate unbounded cost — and no one knows until the invoice arrives or the data breach surfaces.

Controls

What RequestRocket Adds

Integrate with Your IAM

Authenticate AI agents using your existing identity provider — Auth0, Okta, Entra ID, Cognito, or any OIDC-compliant IdP. Issue JWTs from your IdP and validate them at the proxy via JWKS. Each agent gets a verifiable identity without building custom auth into agent code.

Authentication →

Rules, Metering & Limiting

Restrict which endpoints each agent can call using declarative allow/deny rules that match on method, path, headers, body, and JWT claims. Layer meters on top to cap request volume or extracted values (token counts, cost) per minute, hour, day, or month.

Authorization →

Model Routing & Overrides

Use request transforms to route agents to different model endpoints based on request content, agent identity, or cost policy. Override model parameters, inject system prompts, or redirect to a cheaper model dynamically — without changing the agent's code or configuration.

Data Transformation →

Data Redaction

Strip PII, internal identifiers, system metadata, and any fields that should never enter an agent's context window. Filters apply before the response reaches the agent, so sensitive data never leaves the proxy boundary. Layered across credentials, proxies, and targets.

Data Redaction →

Agent Observability & Governance

Every agent MCP / API call produces a full audit record — timing, credential identity, rule evaluations, meter outcomes, filter actions, and response status. Stream to your SIEM for compliance. Dashboard analytics surface anomalies, cost trends, and usage patterns per agent.

Observability →

Credential Isolation

The upstream credential — whether it's an OpenAI key, a database token, or a SaaS secret — is stored encrypted in RequestRocket and injected at the proxy. Agents never see it. Rotate or revoke the upstream credential without touching any agent deployment.

Authentication →

Architecture

How It Works

Point your agents at a RequestRocket proxy instead of the upstream MCP / API directly. The proxy handles identity, policy, and governance — your agents stay simple.

1

Create a proxy per upstream service

Point each proxy at the MCP / API your agents need — an LLM provider, an internal service, a third-party SaaS endpoint. Store the upstream credential encrypted in the target configuration.

2

Issue per-agent credentials

Mint a proxy credential for each agent — MCP / API key, bearer token, or JWT validated against your IdP. Attach rules and meters to scope exactly what each agent can do and how much.

3

Configure transforms & filters

Add request transforms to route models or inject parameters. Add filters to strip sensitive fields from responses. Add response transforms to reshape payloads before they reach the agent.

4

Monitor, iterate, govern

Watch traffic in the dashboard. Stream audit records to your SIEM (Enterprise). Tighten rules, adjust meters, and rotate credentials — all through the core API, no agent redeployment required.

Not sure where your API risk is?Free 15-question assessment aligned to OWASP, SOC 2 & ISO 27001.
Take the API Security Assessment

Use Cases

Common AI Agent Security Scenarios

Practical patterns for governing AI agent access to APIs — from identity integration to cost control and compliance.

Enhance ISO 27001
Enhance SOC 2
Enhance GDPR
Enhance HIPAA

Add outbound API security
without changing code

Start on your own or talk to our team about improving the security of every API call you make.