Technology Comparison

Cequence AI Gateway vs.
Google Apigee: Agentic AI Security Comparison

Google Apigee is one of the most established API management platforms in the enterprise. With MCP support and Model Armor integration, Apigee now positions itself as a unified AI Agent Gateway. Cequence AI Gateway was purpose-built to govern the connection between AI agents and enterprise applications. Both route MCP traffic. They approach the problem from fundamentally different directions.

The Core Distinction

Cequence AI Gateway Google Apigee
What it is Purpose-built AI gateway for governing how agents interact with enterprise apps and data via MCP. API management platform with MCP proxies and Model Armor for AI governance.
Where it sits Between AI agents and your backend services. Between any client and any service. AI/MCP is one of many use cases.
Boundary Agent-to-application (security-first) API traffic management (infrastructure-first)
Apigee is an API management platform that added AI. Cequence is an AI gateway built for security.

Which Problem Are You Actually Solving?

Scenario A: You already run Apigee and want to add MCP routing. Apigee’s MCP proxies handle this with protocol transcoding and 30+ policies. The question is whether policy-based governance is enough, or whether you also need Agent Personas, behavioral forensics, and a security architecture designed specifically for agentic AI.
Scenario B: You are deploying agentic AI and need governed access to enterprise applications. You need purpose-built governance, not proxy policies on a general-purpose platform. This is Cequence.
Scenario C: Both. Cequence and Apigee already coexist at enterprise customers in the API world. Apigee routes API traffic. Cequence protects the applications and APIs that traffic reaches. The same relationship applies to agentic AI.

When to Use Each Technology

Use Cequence AI Gateway When:

Your AI agents need governed access to enterprise applications and data, and you need to control what they do at the tool-call level.
 
Scenario 1: Making APIs and SaaS Apps Agent-Ready
Three paths: convert from OpenAPI spec, import from the application protection platform, or import remote official MCP servers into the governed registry. Prebuilt tools for common enterprise SaaS. Apigee converts APIs to MCP proxies from OpenAPI specs but has no prebuilt SaaS connectors and does not import remote MCP servers.
 
Scenario 2: Agent Job Descriptions (Personas)
Cequence Personas scope each agent to the intersection of user permissions and allowed tools. Apigee scopes access through API products but has no concept of purpose-scoped agent governance.
 
Scenario 3: Behavioral Forensics on Agent Sessions
Cequence reconstructs the full sequential trail of tool calls and produces targeted recommendations. Apigee provides API analytics and ML anomaly detection, not sequential tool call forensics.
 
Scenario 4: Sensitive Data Detection and DLP (Beta)
Native real-time MCP payload inspection with compliance-mapped detection. Apigee requires Google Cloud DLP and Model Armor (Google Cloud dependency).

Use Google Apigee When:

Your platform team needs a unified control plane for API, LLM, and AI traffic within Google Cloud.
 
Scenario 1: Extending Your Existing Apigee Deployment
MCP proxies let you expose existing APIs as MCP tools without deploying separate MCP servers.
 
Scenario 2: LLM Governance with Model Armor
Token quotas, semantic caching, prompt injection detection, PII redaction on LLM traffic.
 
Cequence AI Gateway offers LLM-layer governance through LLM Registry: credential brokering, model allowlisting, Prompt Guard, DLP, and spend limits, tied to the same Agent Persona and audit system that governs MCP and API traffic.
 
Scenario 3: Multi-Cloud LLM Routing
Route agent traffic to Gemini, GPT, Claude across Google Cloud, Azure, AWS with consistent policies.
 
Scenario 4: API Hub as Centralized API Registry
Centralized registry for all APIs including MCP. AI-enhanced documentation.

When You Need Both

Cequence and Apigee already coexist and complement each other at enterprise customers in the API world. That same relationship carries into agentic AI. Apigee manages your API and LLM infrastructure. Cequence governs what AI agents do with your enterprise applications.

Detailed Capability Comparison

Capability Cequence AI Gateway Google Apigee
Primary function Governed connection between agents and enterprise apps/data via MCP. API management platform with MCP proxy support and LLM governance.
Architecture Purpose-built for agentic AI security. MCP-native. Policy-based API proxy. MCP via proxy generation from OpenAPI specs.
API to MCP conversion No-code from OpenAPI spec. Import from app protection platform. Prebuilt tools for common enterprise apps. MCP proxy generation from OpenAPI specs. Protocol transcoding. No prebuilt SaaS connectors.
Remote MCP server import Import remote official MCP servers into governed registry. Centrally managed, governed, monitored. No. Generates own MCP proxies internally. Does not import remote servers.
Enterprise MCP registry Centralized trusted registry. No shadow MCP. No agent-discovered endpoints. API Hub registers MCP APIs. Centralized catalog but not a governed security registry.
API registry Brokers API credentials so agents never hold them directly. Every call runs through the same policy-enforced identity as MCP and LLM traffic. Partial. API Hub catalogs and manages API products, but credentials aren't brokered per agent identity.
Skills registry Curated, vetted, reusable agent capabilities that security and platform teams approve once and reuse across every agent. No equivalent.
AI/LLM/shadow discovery AI Discovery surfaces every agent, LLM provider, and MCP server running across the enterprise, pulled from existing SIEM logs, whether or not it went through an official process. API Hub catalogs registered APIs and MCP proxies. No SIEM-based discovery of shadow agents or shadow LLM usage.
Agent Personas Per-user, per-tool, and per-model scoping. Job descriptions that bind each agent's tools, APIs, and approved model to one policy-enforced identity. Always a reduction, never an expansion. No. API product scoping with OAuth. Access control, not purpose governance.
Sensitive data / DLP Native. Real-time inspection across MCP tool calls, API requests, and LLM prompts and responses, including base64 and evasion-pattern Unicode detection. Compliance-mapped. Block, redact, alert. Via Google Cloud DLP and Model Armor. PII detection, prompt injection. Google Cloud dependency.
Prompt injection protection Prompt Guard detects prompt injection, jailbreak attempts, and system-prompt extraction on every LLM prompt and response. Partial. Model Armor detects prompt injection in LLM traffic. No agent-tool-call-level containment.
Behavioral detection Sequential tool call forensics. Full agent behavioral trail. 10+ years of API attack data. ML-powered API anomaly detection. Analytics dashboards. Not forensics.
LLM governance Partial. Brokers credentials across approved LLM providers, allowlists models per Agent Persona, and enforces spend and rate limits with Prompt Guard and DLP on every call. Yes. Token quotas, semantic caching, Model Armor, multi-cloud routing.
Enterprise IdP OAuth 2.1. Okta, Entra ID, Google. Two-layer credential isolation. OAuth 2.0, API keys, JWT, Google IAM. Broad auth policy support.
Deployment SaaS or self-hosted (Kubernetes). Fully managed on Google Cloud. Hybrid for on-prem/multicloud.
Cloud dependency Platform-independent. Any cloud. Strongest within Google Cloud. Model Armor, DLP, API Hub are GCP services.

Security Considerations

Standards Authorship

Cequence co-authors CIS Controls companion guides for AI Agent and MCP environments with the Center for Internet Security. Three consecutive Verizon DBIRs (2023-2025). Apigee has no comparable standards authorship in agentic AI security.

API Routing vs. API Security and Protection

Apigee routes and manages API traffic. Cequence protects the applications and APIs that traffic reaches. Cequence processes 10 billion+ API interactions per day and understands how APIs actually behave in production. When an agent is not overtly malicious but operates outside expected boundaries, Apigee sees valid authenticated calls. Cequence sees the behavioral pattern: guessing, hallucinating, repeating failures across sessions. That is the difference between routing traffic and protecting applications.

Agent Identity vs. Agent Purpose

Apigee authenticates via OAuth/JWT and scopes access through API products. It answers “is this agent authorized.” Cequence Personas answer “what is this agent’s job, and is it doing only that job right now.” A coerced agent that can only see two read-only tools cannot exfiltrate from the other 16.

Prompt Injection Containment

Prompt injection is unsolved. The “Agents of Chaos” study compromised all six test agents via social engineering. Google DeepMind achieved 86% attack success rates. Apigee’s Model Armor detects injection in LLM prompts. Cequence ensures a coerced agent can only see the tools its Persona permits. When detection fails, containment prevents material harm.

Shadow AI and Agentic Discovery

AI Discovery surfaces every agent, LLM provider, and MCP server running across the enterprise from existing SIEM logs, whether or not it went through an official process — visibility into activity that never touched API Hub’s registered catalog.

Case Study: When an Agent Goes Rogue to Get the Job Done

Environment: Fortune 50 enterprise. Autonomous AI coding agent. 47 continuous hours. 2,575 tool calls. Entirely unsupervised.
What actually happened: The agent guessed 162 filenames. None existed. It hallucinated commit hashes over 71-second loops. It re-probed wrong paths across 27 hours with no memory between sessions.
This is not a malicious agent. It is a determined one.
What Cequence did: Reconstructed the full behavioral trail. Identified six error clusters. Projected error reduction from 212 to under 20 per 48-hour window.
Apigee would show API analytics: request counts, latency, error rates, ML anomaly flags. It would not reconstruct the sequential behavioral trail.

Summary

Apigee is a strong API management platform from Google Cloud. It excels at API governance, LLM traffic management, multi-cloud routing, and Model Armor integration. For platform teams that already run Apigee, MCP proxy generation is a natural extension.
 
But proxy-based MCP routing is table stakes. The security controls are the hard part: Agent Personas, behavioral forensics, sensitive data detection across MCP, API, and LLM traffic, a trusted registry, and the ability to import remote official MCP servers under centralized governance. Cequence and Apigee already coexist at enterprise customers in the API world, and the agentic AI world doesn’t change that arrangement.