Audrey

Audrey is a local-first persistent memory layer for AI agents (including Claude Code). It encodes episodic events into a SQLite-backed store (with vector search via sqlite-vec), recalls relevant memories per prompt, and runs maintenance (“dream”/consolidation) to consolidate episodes into semantic/procedural knowledge with confidence decay and contradiction/validation handling. It can be used as a JS SDK, an MCP server with Claude Code memory tools, a CLI with lifecycle hooks, and a local REST API server.

Evaluated Mar 30, 2026 (0d ago)
Homepage ↗ Repo ↗ Ai Ml agents ai memory persistent-memory mcp claude-code sqlite vector-search rest-api sdk local-first consolidation contradiction-detection
⚙ Agent Friendliness
59
/ 100
Can an agent use this?
🔒 Security
50
/ 100
Is it safe for agents?
⚡ Reliability
34
/ 100
Does it work consistently?

Score Breakdown

⚙ Agent Friendliness

MCP Quality
78
Documentation
74
Error Messages
0
Auth Simplicity
85
Rate Limits
20

🔒 Security

TLS Enforcement
60
Auth Strength
55
Scope Granularity
20
Dep. Hygiene
45
Secret Handling
70

REST server supports Bearer token auth via AUDREY_API_KEY, but the README does not document TLS requirements, authorization model, or fine-grained permissions. Secrets are referenced via environment variables for LLM/embeddings (good practice implied), but there’s no stated guidance on avoiding secret leakage in logs. Local-first storage reduces external data exposure, yet consolidation/embeddings may transmit data to external providers if configured.

⚡ Reliability

Uptime/SLA
0
Version Stability
55
Breaking Changes
45
Error Recovery
35
AF Security Reliability

Best When

You want local, reviewable agent memory on a single machine (or per-user deployment) with MCP/CLI hooks for Claude Code, plus optional embeddings/LLM providers for consolidation and maintenance.

Avoid When

You need centralized managed memory with enterprise-grade tenancy controls, or you cannot accept that embeddings/LLM consolidation may call external providers (when configured).

Use Cases

  • Local, durable memory for multi-session AI agents (especially Claude Code)
  • Per-prompt semantic memory injection to improve context continuity
  • Consolidating session learnings into reusable principles/workflows (dream/consolidation)
  • Detecting/handling contradictory facts and tracking resolution state
  • Building agent applications needing reviewable, exportable memory snapshots (JSON)
  • Standalone memory backend for any framework via REST API

Not For

  • A compliance boundary (must be paired with app-level access control and audit/retention controls)
  • High-availability, multi-region production storage without additional infrastructure (it’s local-first)
  • Use cases requiring strict external data residency controls without hosting guarantees
  • Teams needing a strongly standardized, published OpenAPI/typed contract beyond what the CLI/README describes

Interface

REST API
Yes
GraphQL
No
gRPC
No
MCP Server
Yes
SDK
Yes
Webhooks
No

Authentication

Methods: API key via AUDREY_API_KEY (Bearer token) for REST server
OAuth: No Scopes: No

Auth is mentioned for the REST server using a single Bearer token environment variable. The README does not describe fine-grained scopes/permissions for tools.

Pricing

Free tier: No
Requires CC: No

No hosted service pricing is described; package is local-first.

Agent Metadata

Pagination
none
Idempotent
False
Retry Guidance
Not documented

Known Gotchas

  • Memory is stored locally in a SQLite file; concurrent agent/worker access may require careful process coordination (not documented here).
  • REST server appears local (default port 3487); exposing to networks without strong deployment security may be risky.
  • When using hosted embeddings/LLMs for consolidation, failures/timeouts and provider rate limits should be handled by the integrator (no explicit retry/rate-limit guidance described in README).
  • Because embeddings are re-generated on snapshot restore, cost/latency can spike depending on embedding provider configuration.

Alternatives

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Scores are editorial opinions as of 2026-03-30.

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