AgentGate vs Google Cloud Model Armor

AgentGate

An agent or its host can send each tool call to one REST endpoint, or wrap an MCP server, and get allow, deny or ask from a local classifier and a YAML policy, with an audit log and approval queue. The project is three days old, auth is off by default, and no detection accuracy is published.

Google Cloud Model Armor

2 million free tokens a month, then $0.10 per million. OAuth only, and a template must exist in the same location as the endpoint before the first call.

AgentGate

1. Create a session with the user's real goal first. The goal-alignment head scores every later call against it
2. Pass earlier tool results in history_override with untrusted: true for web or email content, or the injection head sees only the action
3. On ask, stop and tell the user the decision_id. Polling /v1/decisions/:id needs the dashboard key
4. Treat allow_with_checkpoint as allow and keep the checkpoint_id for an undo
5. Expect HTTP 404 with not_found for an unknown session and 401 when the owner has set an agent key

Google Cloud Model Armor

1. Create one template per location you call from. A template in us-central1 doesn't answer on the europe-west2 endpoint
2. Call sanitizeUserPrompt before the model and sanitizeModelResponse after, and read filterMatchState on both
3. Treat EXECUTION_SKIPPED as unchecked, not clean. It means the input went over the filter's 65,536-token cap
4. Pin the template to the Stable alias and move off v1 and v2 before 17 December 2026. In asia-northeast3, v1 stays the Stable version
5. Retry 500, 502, 503 and 504 with truncated exponential backoff, and keep fan-out under the 1,200 queries a minute shared by the project