MemoryAtlas

A modular multi-agent memory system that augments any LLM. Specialized agents manage six memory types (Core, Episodic, Semantic, Procedural, Resource, Knowledge Vault) under a coordinator that orchestrates updates and retrieval. Ships a desktop app that builds a personal memory base from on-screen activity.

Storage
Typed memory stores for the six memory categories; local storage for the packaged app to keep data on-device.
Retrieval
A coordinator routes queries to the relevant memory-type agents and consolidates results; operates as an external system, not a model plugin.
Self-host
Self-host: moderate
License
Apache-2.0
Pricing
Open source (Apache-2.0), free to self-host · Free / OSS
GitHub stars
3,549
Last release
2025-12-25
Last commit
2026-06-20
First catalogued
2026-06-28

Strengths

  • Multi-agent design with six distinct memory types
  • Model-agnostic — augments any LLM as an external system
  • Ships a working personal-assistant app with local storage

Watch out

  • No tagged GitHub releases yet; versioning/stability unclear
  • A hosted offering may exist (mirix.io); managed pricing not confirmed
  • Self-reported LoCoMo/ScreenshotVQA numbers exist — route to harvest-benchmarks, do not treat as neutral here

Best for

  • Personal assistants needing multimodal, screen-aware long-term memory

Benchmark results

BenchmarkValueBackboneTrustSource
locomo85.38 accuracygpt-4.1-miniSelf-reportedMIRIX (Wang & Chen)
longmemeval43.49 accuracyGPT-4o-miniIndependentMemOS (MemTensor) — competitor re-run

Sources

Last verified 2026-06-28 · updated by manual-refresh