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Memorius is a self-contained, agent-agnostic memory system that gives LLMs and AI agents persistent, searchable memory with a hierarchical knowledge organization. Drop-in with multi-backend vector storage, pluggable embeddings, built-in MCP + REST servers, and auto-detecting agent hooks for 7 different AI coding agents.

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Memorius

memorius

Universal memory vault for any AI agent.

PyPI version Tests PyPI publish MIT license Python 3.11 | 3.12 Changelog

Works with Claude Code, Codex CLI, Gemini CLI, OpenClaude, OpenCode, Pi, OpenClaw, and any MCP-compatible agent.

📚 Documentation: https://dream-pixels-forge.github.io/memorius/ — install, CLI reference, MCP server, hooks, REST API, architecture, and the memory engine, all on the site.

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Memorius is a self-contained, agent-agnostic memory system with hierarchical knowledge organization, pluggable embeddings, and neuroscience-inspired consolidation. One vault, many frontends — CLI, MCP, REST, and auto-detecting agent hooks. No cloud, no API keys, no lock-in.

Install

pip install memorius

All features — vector search, cross-encoder reranker, REST API server, SQLite-vec backend, OpenAI embeddings, knowledge graph, and the agent skill — are included out of the box. No extra install flags needed.

Verify:

memorius --version
memorius init          # creates ~/.memorius/config.yaml + storage dir

CLI Reference

memorius stats

Show vault + memory + graph statistics --json Output as JSON

memorius status

Show vault status --json Output as JSON

memorius bookcase

Launch the 3D walkable vault bookcase (browser opens automatically, loopback only). --port REST API port (default: 8912) --static-port Static asset port for the bookcase page (default: 8400) --no-browser Don't open the browser; just serve the page

Vault Bookcase (3D walkable)

Run the bookcase:

memorius bookcase

It starts the REST API on http://127.0.0.1:8912, serves the bookcase page on http://127.0.0.1:8400/bookcase.html, and opens your browser. Everything is loopback-only — nothing leaves your machine.

Use memorius bookcase --no-browser to serve without opening a tab, then open the printed URL yourself. Use --port / --static-port if the defaults are taken.

Once the page is open:

  • Walk: WASD or arrow keys at eye height. You can't pass through shelves.
  • Look: click-drag to look around (pointer-lock if available).
  • Vault: pick a vault from the dropdown (options come from GET /vaults).
  • Layout: switch between "by shelf" and "by recency" to re-arrange cases.
  • Search: type in the vault search bar and hit Enter/Go — the camera flies to the matching book and marks it.
  • Book click: click a book to open its detail panel (content + librarian speech when the Librarian toggle is on).
  • Mic: hold the mic button to speak your search (Chromium only).
  • Reset view: click ⟲ view to return to the starting camera position.

The librarian reads each book aloud when toggled on; all utterances are also logged in the guidance panel on the page.

For development
pip install "memorius[dev]"   # adds pytest + pytest-asyncio

Quick start

# Initialize a vault
memorius init

# Store a memory
memorius store "The sky is blue because Rayleigh scattering scatters shorter wavelengths more" \
  --vault main --shelf science --folder physics

# Semantic search
memorius search "why is the sky blue"

# Mine memories from a conversation
memorius mine transcript.txt --vault conversations

# Check status
memorius status

That's the whole loop: store → embed → search. Read the Getting Started guide for the vault hierarchy, the agent skill, and a recommended first-week flow.

Documentation

The full docs live on the site — each concern on its own page:

Page What's on it
Getting Started Install, init, first memory, the Vault→Shelf→Folder→Note hierarchy, agent skill
CLI Reference Every subcommand and flag (incl. repair and --json)
MCP Server All 29 tools + per-agent client config snippets
Agent Hooks Auto-detecting lifecycle hooks, 10 actions, normalizers, security
REST API Full endpoint table, auth, rate limits, daemon mode, TLS
Architecture Search pipeline, embeddings, vector backends, graph, configuration
Agent Compatibility Which agents, detection priority, how to plug in your own
Memory Engine Decay, consolidation, pruning, fact-checking, reranking, doctor, repair
Command cheat sheet (details on the CLI reference)
memorius store "text" [--vault/--shelf/--folder/--note/--ttl]
memorius search "query" [--n/--expand-graph/--rerank/--web/--tag]
memorius mine file.txt [--vault/--text]
memorius extract file.txt [--backend openai|ollama|regex]
memorius diary "session" [--title/--summary]
memorius ls [vault]
memorius consolidate [--threshold/--dry-run]
memorius factcheck "stmt" [--web]
memorius profile "session"
memorius prune [--threshold/--dry-run/--delete]
memorius graph [view|export-html|stats|json]
memorius learn "text" --category bug_fix
memorius recall "query"
memorius obsidian [list|import|export]
memorius export ./backup [--format json|markdown]
memorius import ./backup.json [--replace]
memorius doctor            # 6 health checks
memorius repair [--reindex/--dry-run]   # fix vector/meta drift (v0.8.6)
memorius stats [--json]      # vault + memory + graph + doctor summary
memorius status [--json]    # vault + embeddings + recent diaries
memorius serve               # MCP server (stdio)
memorius serve-rest [--daemon/--stop]   # FastAPI server

License

MIT · Full release history in CHANGELOG.md.

About

Memorius is a self-contained, agent-agnostic memory system that gives LLMs and AI agents persistent, searchable memory with a hierarchical knowledge organization. Drop-in with multi-backend vector storage, pluggable embeddings, built-in MCP + REST servers, and auto-detecting agent hooks for 7 different AI coding agents.

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