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ori-memory
Advanced tools
Persistent memory for AI agents — local-first, markdown-native, no cloud. Knowledge graph + three-signal retrieval (semantic + BM25 + PageRank). Agents wake up knowing who they are across sessions. MCP server for Claude, Cursor, Windsurf, Cline.
Open-source persistent memory for AI agents.
Install it on any machine, point your agent at it, and it wakes up knowing who it is. Not because you pasted context into a system prompt. Because it has a memory system that learns what matters, forgets what doesn't, and keeps your agent's knowledge in files you own.
Markdown on disk. Wiki-links as graph edges. Git as version control. No database, no cloud, no lock-in.
v0.3.3 · npm package · Apache-2.0
npm install -g ori-memory
ori init my-agent
cd my-agent
Add to any MCP client (Claude Code, Cursor, Windsurf, Cline, or your own agent loop):
{
"mcpServers": {
"ori": {
"command": "ori",
"args": ["serve", "--mcp"]
}
}
}
Start a session. The agent receives its identity automatically and begins onboarding on first run.
Persistent identity. Agents wake up as themselves. Name, personality, goals, methodology travel with the vault across sessions, clients, and machines.
Three-signal retrieval. Not just vector search. Semantic embeddings + BM25 keyword matching + PageRank graph importance, fused through Reciprocal Rank Fusion with automatic intent classification. ~850 tokens per query regardless of vault size.
Knowledge graph. Every [[wiki-link]] is a graph edge. PageRank authority, Louvain community detection, betweenness centrality, orphan and dangling link detection. Structure is queryable.
Graph-aware forgetting. Notes decay using ACT-R cognitive science. Used notes stay alive. Their neighbors stay warm through spreading activation along wiki-link edges. Structurally critical nodes are protected by Tarjan's algorithm. No other shipped memory system does this.
Zone classification. Notes are active, stale, fading, or archived based on vitality score. ori prune analyzes the full activation topology, identifies archive candidates, and protects articulation points. Dry-run by default.
Capture-promote pipeline. ori add captures to inbox. ori promote classifies (idea, decision, learning, insight, blocker, opportunity), detects links, suggests areas. 50+ heuristic patterns. Optional LLM enhancement.
Zero cloud dependencies. Local embeddings via all-MiniLM-L6-v2 running in-process. SQLite for vectors. Everything on your filesystem. Zero API keys required for core functionality.
Without retrieval, every question requires dumping the entire vault into context. With Ori, the cost stays flat.
| Vault Size | Without Ori | With Ori | Savings |
|---|---|---|---|
| 50 notes | 10,100 tokens | 850 tokens | 91% |
| 200 notes | 40,400 tokens | 850 tokens | 98% |
| 1,000 notes | 202,000 tokens | 850 tokens | 99.6% |
| 5,000 notes | 1,010,000 tokens | 850 tokens | 99.9% |
A typical session costs ~$0.10 with Ori. Without it: ~$6.00+.
Layer 4: MCP Server (14 tools, 5 resources) any agent talks to this
Layer 3: Three-Signal Retrieval Engine semantic + keyword + graph
Layer 2: Knowledge Graph + Vitality Model wiki-links, ACT-R decay, spreading activation
Layer 1: Markdown files on disk git-friendly, human-readable, portable
14 MCP tools. 5 resources. 16 CLI commands. 396 tests (328 unit + 68 integration).
Every vault has three memory spaces with distinct decay rates.
| Space | Path | Decay | What lives here |
|---|---|---|---|
| Identity | self/ | 0.1x | Who the agent is. Name, goals, methodology. Barely decays. |
| Knowledge | notes/ | 1.0x | What the agent knows. Ideas, decisions, learnings, connections. |
| Operations | ops/ | 3.0x | What the agent is doing. Daily tasks, reminders, sessions. Decays fast. |
Identity persists. Knowledge lives and dies by relevance. Operational state burns hot and clears itself.
Any MCP Client
(Claude, Cursor, Windsurf,
Cline, custom agents, VPS)
|
MCP Protocol
(stdio / JSON-RPC)
|
+-------------------+
| Ori MCP Server |
| |
| instructions | identity auto-injected at connect
| resources | 5 readable endpoints (ori://)
| 14 tools | full memory operations
+-------------------+
|
+-------------------+-------------------+
| | |
+-----------+ +------------+ +------------+
| Knowledge | | Identity | | Operations |
| Graph | | Layer | | Layer |
| | | | | |
| notes/ | | self/ | | ops/ |
| inbox/ | | identity | | daily |
| templates| | goals | | reminders |
| | | method. | | sessions |
+-----------+ +------------+ +------------+
|
+-----+------+
| |
Wiki-link Embedding
Graph Index
(in-memory) (SQLite)
| |
PageRank Semantic
Spreading Search
Activation BM25
Communities 3-Signal Fusion
| Tool | What it does |
|---|---|
ori_orient | Session briefing: daily status, goals, reminders, vault health |
ori_update | Write to identity, goals, methodology, daily, or reminders |
ori_status | Vault overview |
ori_health | Full diagnostics |
ori_add | Capture to inbox |
ori_promote | Promote with classification, linking, and area assignment |
ori_validate | Schema validation against templates |
ori_query | Graph queries: orphans, dangling, backlinks, cross-project |
ori_query_ranked | Three-signal retrieval with spreading activation |
ori_query_similar | Semantic search (vector only, faster) |
ori_query_important | PageRank authority ranking |
ori_query_fading | Vitality-based decay detection |
ori_prune | Activation topology and archive candidates |
ori_index_build | Build or update the embedding index |
# Vault management
ori init [dir] # Scaffold a new vault
ori status # Vault overview
ori health # Full diagnostics
# Note lifecycle
ori add <title> [--type <type>] # Capture to inbox
ori promote [note] [--all] # Promote to knowledge graph
ori validate <path> # Schema validation
ori archive [--dry-run] # Archive stale notes
ori prune [--apply] [--verbose] # Topology analysis + archive candidates
# Retrieval
ori query orphans # Notes with no incoming links
ori query dangling # Broken wiki-links
ori query backlinks <note> # What links to this note
ori query cross-project # Multi-project notes
ori query ranked <query> # Three-signal retrieval
ori query similar <query> # Semantic search
ori query important # PageRank ranking
ori query fading # Vitality detection
# Infrastructure
ori index build [--force] # Build embedding index
ori index status # Index statistics
ori graph metrics # PageRank, centrality
ori graph communities # Louvain clustering
ori serve --mcp [--vault <path>] # Run MCP server
ori bridge claude-code [--global] # Install Claude Code hooks
vault/
├── .ori # Vault marker
├── ori.config.yaml # Configuration
├── notes/ # Knowledge graph (flat, no subfolders)
│ └── index.md # Hub entry point
├── inbox/ # Capture buffer
├── templates/ # Note and map schemas
├── self/ # Agent identity
│ ├── identity.md # Name, personality, values
│ ├── goals.md # Active threads, priorities
│ ├── methodology.md # Processing principles
│ └── memory/ # Agent's accumulated insights
└── ops/ # Operational state
├── daily.md # Today's completed and pending
├── reminders.md # Time-bound commitments
└── sessions/ # Session logs
Every file is plain markdown. Open it in any text editor, Obsidian, or your file browser. git log is your audit trail.
Local. Install globally, ori init, connect your MCP client. Done.
VPS / headless. Install on the server. ori serve --mcp --vault /path/to/vault. Memory persists on the filesystem. Back up with git push.
Multi-vault. Separate Ori instances for separate agents. Each vault is self-contained: its own identity, knowledge graph, and operational state.
Scriptable. CLI returns structured JSON. Use in cron jobs, webhook handlers, or orchestration loops.
ori.config.yaml controls all tunable parameters. Generated with sensible defaults on ori init.
| Section | Controls |
|---|---|
vitality | Decay parameters, metabolic rates, zone thresholds, bridge bonus |
activation | Spreading activation: damping, max hops, min boost |
retrieval | Signal weights, exploration budget |
engine | Embedding model, database path |
promote | Auto-promotion, project routing |
llm | Optional: Anthropic, OpenAI-compatible, or local models |
LLM integration is optional. Every operation works deterministically with heuristics alone. When configured, LLM improves classification and link suggestions.
Most memory systems store your agent's knowledge in infrastructure you do not control. A proprietary database. A cloud service. A vendor's format.
Ori stores memory as files you own. The vault is portable. Move it to a new machine, push it to a git remote, open it in a text editor. Switch MCP clients by changing one config line. The memory survives any platform change because it was never locked to a platform.
This is not ideological. It is architectural. Portable memory is composable memory.
git clone https://github.com/aayoawoyemi/Ori-Mnemos.git
cd Ori-Mnemos
npm install
npm run build
npm link
ori --version
npm test # 396 tests
npm run lint # Type check
npm run dev # Watch mode
Apache-2.0
Memory is sovereignty. Ori gives your agent workflow life.
FAQs
Cognitive architecture for persistent AI agent memory. Knowledge graph with learning retrieval, ACT-R decay, and spreading activation. Markdown-native, local-first, zero cloud. MCP server + CLI.
The npm package ori-memory receives a total of 80 weekly downloads. As such, ori-memory popularity was classified as not popular.
We found that ori-memory demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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