memory-os
A 7-layer memory operating system for Hermes Agent with persistent memory and context injection
GraphCanon updated 4w · GitHub synced 4w
Decision brief
Memory-OS is a memory operating system tailored for Hermes Agent, focusing on local-first, self-hosted persistent storage and seamless integration with any LLM provider using Qdrant as the vector database.
Good fit when
- - You are working with Hermes Agent and require a sophisticated memory management solution that operates locally.
- - Your project involves the need for surgical context injection into the AI processes to enhance precise fact recall.
Avoid when
- - If you are looking for a completely cloud-managed service without any local setup or maintenance needs.
- - Your use case does not align with Hermes Agent; Memory-OS is specifically designed to complement this agent's functions and won't provide the same benefits when used independently.
Observed Jul 12, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Steady (41d since push)
- As of 4w
- Provenance
- Not a fork · Personal account
- As of 4w
- Security (OSV)
- No lockfile
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install memory-os PyPIHow it fits your stack(11)
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Overview
Provides a memory operating system that supports local-first, self-hosted persistent storage of structured facts using Qdrant as the vector database. Supports integration with any LLM provider.
Capability facts
- Languages
- python
Source: github.language · Jul 22, 2026
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Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Jul 22, 2026)
**Requirements:** Hermes Agent + Docker (Qdrant + Redis + ARQ Worker) + Python 3.11+.Source link
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README
Memory OS — Hermes Agent Memory Operating System
Your agent finally stops forgetting.
Permanent memory. Local memory infrastructure. API-provider agnostic. Surgically token-efficient.
Seven memory layers. Automatic, intelligent context injection. Structured facts with trust scoring. A self-curating wiki pipeline. Semantic search across every conversation you've ever had.
Memory OS turns Hermes Agent into a real long-term collaborator — one that remembers your projects, your decisions, your reasoning, and brings exactly the right context back at exactly the right moment. Like talking to a colleague who was there for every session.
Memory infrastructure runs entirely on your machine. Works with any LLM provider — OpenRouter, OpenAI, Anthropic, Ollama, or local models. No memory subscription. No vendor lock-in.
What's New in v0.2.0
One-command install. curl -sSL https://raw.githubusercontent.com/ClaudioDrews/memory-os/main/setup.sh | bash sets up the entire stack — Docker services, SQLite databases, Icarus plugin, environment — in one shot. The 10-step manual guide is now a fallback for troubleshooting.
Community infrastructure. Issue templates (bug report + feature request), PR checklist, and contributing guide. Project is ready for external contributors — and already has them.
20+ fixes from systematic audit. Community-driven review across setup, configuration, performance, and resilience. Highlights: provider-agnostic LLM extraction, O(1) path lookups, FTS5-powered session search, semantic dedup at scale, and idempotent database initialization.
Installation verified on real hardware. Smoke tests and ingestion tests ship with the repo. The automated installer has been tested end-to-end — including on modest machines where Docker build times exposed UX gaps that are now handled gracefully.
The problem every serious Hermes user knows
You spend hours configuring the agent, teaching it your preferences, solving hard problems together — and in the next session it acts like it's meeting you for the first time.
- Repeating context at the start of every conversation
- Losing the thread of important decisions made weeks ago
- Structured facts — your stack, your projects, your patterns — with nowhere to live
- Every memory solution you've tried is either cloud-locked or too shallow to matter
After months of hitting these walls in production, I built something that actually works.
What Memory OS is
Not just another plugin. A complete memory operating system — 7 layers working in concert, from flat files to a vector database, with surgical context injection, a knowledge pipeline that organizes itself, and an explicit Ground Truth hierarchy that tells the agent to actually use the injected memory.
Designed and refined by someone who ran headfirst into every limitation of stock Hermes and every existing memory solution.
Requirements: Hermes Agent + Docker (Qdrant + Redis + ARQ Worker) + Python 3.11+.
Compatible with any LLM provider Hermes supports — OpenRouter, OpenAI, Anthropic, Ollama, and more.
Architecture: 7 memory layers
┌──────────────────────────────────────────────────────────────────┐
│ LAYER 1 · WORKSPACE │
│ MEMORY.md · USER.md · CREATIVE.md │
│ → Injected into the system prompt every single turn │
├──────────────────────────────────────────────────────────────────┤
│ LAYER 2 · SESSIONS │
│ state.db (SQLite + FTS5) │
│ → Full-text search across your entire conversation history │
├──────────────────────────────────────────────────────────────────┤
│ LAYER 3 · STRUCTURED FACTS │
│ memory_store.db (SQLite + HRR + FTS5 + trust scoring) │
│ → Durable facts with entity resolution and an automat
For agents
This page has a .md twin and JSON over the API.