ZenBrain Memory MCP server

ZenBrain The neuroscience-inspired memory system for AI agents. 7 memory layers. Real neuroscience — FSRS, Hebbian, sleep consolidation, 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. Zero dependencies. 528 tests. Extracted from a production AI platform.

Status: pre-1.0, semver — the public API can still change before 1.0. 528 tests green on Node 22, 24 and 26 in CI · every release published to npm with build provenance · every change recorded in the CHANGELOG · issues and pull requests get a first response typically within 72 hours.

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

📄 Paper & Citation — ZenBrain: A Neuroscience-Inspired 7-Layer Memory Architecture for Autonomous AI Systems

• 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.

Your AI forgets everything after every conversation. ZenBrain fixes that — with the same mechanisms your brain uses: spaced repetition, emotional consolidation, Hebbian strengthening, and exponential forgetting curves. Not a vector database with a wrapper. Actual neuroscience.

Architecture vs. this package. ZenBrain's architecture is 15 neuroscience-inspired mechanisms — 9 foundational algorithms + 6 Predictive Memory Architecture (PMA) components (paper). The 6 PMA components are proprietary and run in the production system. This open-source package ships the algorithm library: 10 core algorithms + 10 advanced research modules (20 modules), zero-dependency.

Benchmark: LongMemEval-500

Shortened. The full README is on GitHub.