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Trust infrastructure for AI agents

Mnemom makes AI agent behavior transparent and verifiable. When an agent makes a decision, Mnemom records what it decided, what alternatives it considered, what values it applied, and whether its reasoning was compromised. The result is a verifiable audit trail that any stakeholder can inspect. Two open-source protocols power this:
  • AAP (Agent Alignment Protocol) — Post-hoc verification. Alignment Cards declare an agent’s values and boundaries. AP-Traces record every decision. Verification checks whether behavior is consistent with declared intent.
  • AIP (Agent Integrity Protocol) — Real-time integrity checking. Analyzes LLM thinking blocks during execution to detect prompt injection, value drift, and manipulation before the agent acts.
These are transparency protocols, not trust protocols. They make agent behavior observable and auditable — they do not guarantee trustworthiness. An agent that passes all checks may still behave badly in ways the protocols cannot detect. See the limitations docs for what AAP and AIP can and cannot guarantee.

Get started

Key concepts

SDK packages

Install the protocol SDKs directly if you need fine-grained control:
npm install @mnemom/agent-alignment-protocol
npm install @mnemom/agent-integrity-protocol
PackageLanguageRegistryDescription
@mnemom/agent-alignment-protocolTypeScriptnpmAAP verification, coherence, drift detection
@mnemom/agent-integrity-protocolTypeScriptnpmAIP integrity checking, signal building
agent-alignment-protoPythonPyPIAAP verification, coherence, drift detection
agent-integrity-protoPythonPyPIAIP integrity checking, signal building

Protocols