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@iflow-mcp/evilander-audrey

v0.17.0

Published

Biological memory architecture for AI agents - encode, consolidate, and recall memories with confidence decay, contradiction detection, and causal graphs

Readme

Audrey

CI npm version License: MIT

Audrey is a persistent memory and continuity engine for Claude Code and AI agents.

It gives an agent a local memory store, durable recall, consolidation, contradiction handling, a REST sidecar, MCP tools, and benchmark gates without adding external infrastructure.

Requires Node.js 20+.

Quick Start

Claude Code

npx audrey init
npx audrey doctor

This uses the default local-offline preset:

  • registers Audrey with Claude Code
  • installs hooks for automatic recall and reflection
  • uses local embeddings by default
  • stores memory in one local SQLite-backed data directory

REST or Docker Sidecar

npx audrey init sidecar-prod
docker compose up -d --build

Then verify:

npx audrey doctor
curl http://localhost:3487/health

Why Audrey

  • Local-first: memory lives in SQLite with sqlite-vec, not a hosted vector database.
  • Practical: MCP, CLI, REST, JavaScript, Python, and Docker are all first-class.
  • Durable: snapshot, restore, health checks, benchmark gates, and graceful shutdown are built in.
  • Structured: Audrey does more than save notes. It consolidates, decays, tracks contradictions, and supports procedural memory.

What Ships

  • Claude Code MCP server with 13 memory tools
  • Automatic hook-based recall and reflection for Claude Code sessions
  • JavaScript SDK
  • Python SDK packaged as audrey-memory
  • REST API for sidecar deployment
  • Docker and Compose deployment path
  • Snapshot and restore for portable memory state
  • Machine-readable health and benchmark gates
  • Local benchmark harness with retrieval and lifecycle-operation tracks

Setup Presets

npx audrey init supports four named presets:

| Preset | Best For | Behavior | |---|---|---| | local-offline | Claude Code on one machine | Local embeddings, MCP install, hooks install | | hosted-fast | Claude Code with provider keys already present | Auto-picks hosted providers from env, MCP install, hooks install | | ci-mock | CI and smoke tests | Mock embedding + LLM providers, no Claude-specific setup | | sidecar-prod | REST API and Docker deployment | Sidecar-oriented defaults, no Claude-specific setup |

Useful checks:

npx audrey doctor
npx audrey status
npx audrey status --json --fail-on-unhealthy

Use Audrey From Code

JavaScript

import { Audrey } from 'audrey';

const brain = new Audrey({
  dataDir: './audrey-data',
  agent: 'support-agent',
  embedding: { provider: 'local', dimensions: 384 },
});

await brain.encode({
  content: 'Stripe returns HTTP 429 above 100 req/s',
  source: 'direct-observation',
  tags: ['stripe', 'rate-limit'],
});

const memories = await brain.recall('stripe rate limit');

await brain.waitForIdle();
brain.close();

Python

pip install audrey-memory
from audrey_memory import Audrey

brain = Audrey(
    base_url="http://127.0.0.1:3487",
    api_key="secret",
    agent="support-agent",
)

memory_id = brain.encode(
    "Stripe returns HTTP 429 above 100 req/s",
    source="direct-observation",
)
results = brain.recall("stripe rate limit", limit=5)
brain.close()

Key Commands

# Setup
npx audrey init
npx audrey init hosted-fast
npx audrey init ci-mock
npx audrey init sidecar-prod

# Claude Code integration
npx audrey install
npx audrey hooks install
npx audrey hooks uninstall
npx audrey uninstall

# Health and maintenance
npx audrey doctor
npx audrey status
npx audrey dream
npx audrey reembed

# Versioning
npx audrey snapshot
npx audrey restore backup.json --force

# Sidecar
npx audrey serve
docker compose up -d --build

Benchmarks

Audrey ships with a benchmark harness and release gate:

npm run bench:memory
npm run bench:memory:check

The benchmark suite measures:

  • retrieval behavior
  • update and overwrite behavior
  • delete and abstain behavior
  • semantic and procedural merge behavior

Current repo snapshot:

Audrey local benchmark

For detailed methodology, published comparison anchors, and generated reports, see docs/benchmarking.md.

Production

Audrey is strongest in workflows where memory must stay local, reviewable, and durable. It already fits well as a sidecar for internal agents in operational domains like financial services and healthcare operations, but it is a memory layer, not a compliance boundary.

Production guide: docs/production-readiness.md

Examples:

Environment

Starter config:

Key environment variables:

  • AUDREY_DATA_DIR
  • AUDREY_EMBEDDING_PROVIDER
  • AUDREY_LLM_PROVIDER
  • AUDREY_DEVICE
  • AUDREY_API_KEY
  • AUDREY_HOST
  • AUDREY_PORT

Documentation

Development

npm ci
npm test
npm run bench:memory:check
npm run pack:check
python -m unittest discover -s python/tests -v
python -m build --no-isolation python

License

MIT. See LICENSE.