logging and auditing AI agents on Google AP2 when they touch money APIs

Google AP2 lets agents interact with third-party tools, including financial APIs. that's powerful — and risky if the agent gets compromised or makes a bad decision.

the missing piece is a logging and auditing layer that records every tool call, policy check, and execution result in a tamper-evident trail.

here's what that looks like for AP2 agents:

1. wrap tool calls with governance middleware — the agent doesn't call the payment API directly. it calls a governance layer that validates the request against spending policies, logs the decision, then forwards approved requests to the underlying API.
2. log every decision — not just executed transactions, but every proposed transaction, policy check, approval decision, and abort reason.
3. merkle-chained audit trail — each log entry is a leaf node in a merkle tree. the root hash is signed and timestamped every 60 seconds.
4. exportable audit bundles — the full chain exports as JSON for regulator or auditor review. a third party can verify the chain without trusting your infrastructure.

this maps directly to EU AI Act Article 12 requirements for high-risk systems — the audit trail has to be tamper-evident and exportable.

i built mnemopay to wrap AP2 tool calls (and other agent platforms) with policy enforcement and audit logging as infrastructure. the SDK handles governance logic, merkle-chained logs, and JSON export so you don't have to roll your own.

the core insight: once agents start touching real money APIs, logging and auditing aren't optional features — they're the foundation of accountability and compliance.

if you're building on AP2, treat the governance and audit layer as a first-class dependency, not a feature you add later.