ZenBrain Memory MCP server

ZenBrain <strong>The neuroscience-inspired memory system for AI agents.</strong> 7 memory layers and a library of 20 neuroscience-inspired algorithm modules: FSRS, Hebbian learning, sleep replay, emotional tagging, plus 10 advanced research modules (vmPFC-FSRS, two-factor Hebbian, simulation-selection sleep, Fiedler-value KG health, IB budget, Hopfield STM, ...).Pure TypeScript. No third-party dependencies in algorithms and core. 945 tests. Extracted from a production AI platform.

_{<strong>Status:</strong> pre-1.0, semver — the public API can still change before <code>1.0</code>. 945 tests green in CI: 933 on each of Node 22, 24 and 26, and 12 more against PostgreSQL with pgvector · the current version of every package published to npm with build provenance · every change recorded in the CHANGELOG · issues and pull requests are answered; replications and counter-results are especially welcome.}

_{<strong>Self-hosted:</strong> the library makes no network calls of its own. Memory lives in SQLite or PostgreSQL that you operate; an embedding model or an LLM is optional and your choice.}

<strong>▶ Try the live playground in your browser</strong> — runs this published code, no install required.

<details> <summary><strong>📄 Paper & Citation</strong> — ZenBrain: A Neuroscience-Inspired 7-Layer Memory Architecture for Autonomous AI Systems</summary>

• arXiv preprint (cs.AI): arxiv.org/abs/2604.23878
• Open-access archive (Zenodo / CERN): doi.org/10.5281/zenodo.19353663
• ORCID: 0009-0001-1793-012X
• License: CC BY 4.0 (paper) · Apache-2.0 (code)

@misc{bering2026zenbrain,
  title         = {ZenBrain: A Neuroscience-Inspired 7-Layer Memory Architecture for Autonomous AI Systems},
  author        = {Bering, Alexander},
  year          = {2026},
  eprint        = {2604.23878},
  archivePrefix = {arXiv},
  primaryClass  = {cs.AI},
  doi           = {10.5281/zenodo.19353663},
  url           = {https://arxiv.org/abs/2604.23878}
}

Feedback, replications, and counter-results are explicitly welcome — please open an issue or reach out via research@zensation.ai.

</details>

Your AI forgets everything after every conversation. ZenBrain gives it a memory that lasts across sessions, split into layers the way human memory is, and ships the mechanisms memory research describes (spaced repetition, emotional tagging, Hebbian strengthening, forgetting curves, sleep replay) as tested functions. Which of them run on their own and which you call yourself is in one table.

Architecture vs. this package. ZenBrain's architecture is 15 neuroscience-inspired mechanisms — 9 foundational algorithms + 6 Predictive Memory Architecture (PMA) components (paper). The six PMA components are proprietary: they ran in the ZenAI production system and are not in these packages, which contain the hooks they plug into. This open-source package ships the algorithm library: 10 core algorithms + 10 advanced research modules (20 modules), zero-dependency.

Benchmark: LongMemEval-500