Content
<p align="center">
<strong>OMEM</strong><br/>
Shared Memory That Never Forgets
</p>
<p align="center">
<a href="https://github.com/ourmem/omem/blob/main/LICENSE"><img src="https://img.shields.io/badge/license-Apache--2.0-blue.svg" alt="License"></a>
<a href="https://ourmem.ai"><img src="https://img.shields.io/badge/hosted-ourmem.ai-green.svg" alt="Hosted"></a>
<a href="https://github.com/ourmem/omem"><img src="https://img.shields.io/github/stars/ourmem/omem?style=social" alt="Stars"></a>
</p>
<p align="center">
<strong>English</strong> | <a href="README_CN.md">简体中文</a>
</p>
---
## The Problem
Your AI agents have amnesia — and they work alone.
- 🧠 **Amnesia** — every session starts from zero. Preferences, decisions, context — all gone.
- 🏝️ **Silos** — your Coder agent can't access what your Writer agent learned.
- 📁 **Local lock-in** — memory tied to one machine. Switch devices, lose everything.
- 🚫 **No sharing** — team agents can't share what they know. Every agent re-discovers the same things.
- 🔍 **Dumb recall** — keyword match only. No semantic understanding, no relevance ranking.
- 🧩 **No collective intelligence** — even when agents work on the same team, there's no shared knowledge layer.
**ourmem fixes all of this.**
## What is ourmem
ourmem gives AI agents shared persistent memory — across sessions, devices, agents, and teams. One API key reconnects everything.
🌐 **Website:** [ourmem.ai](https://ourmem.ai)
<table>
<tr>
<td width="50%" valign="top">
### 🧑💻 I use AI coding tools
Install the plugin for your platform. Memory works automatically — your agent recalls past context on session start and captures key info on session end.
**→ Jump to [Quick Start](#quick-start)**
</td>
<td width="50%" valign="top">
### 🔧 I'm building AI products
REST API with 48+ endpoints. Docker one-liner for self-deploy. Embed persistent memory into your own agents and workflows.
**→ Jump to [Self-Deploy](#self-deploy)**
</td>
</tr>
</table>
## Core Capabilities
<table>
<tr>
<td width="25%" align="center">
<h4>🔗 Shared Across Boundaries</h4>
Three-tier Spaces — Personal, Team, Organization — let knowledge flow across agents and teams with full provenance tracking.
</td>
<td width="25%" align="center">
<h4>🧠 Never Forget</h4>
Weibull decay model manages the memory lifecycle — core memories persist, peripheral ones gracefully fade. No manual cleanup.
</td>
<td width="25%" align="center">
<h4>🔍 Deep Understanding</h4>
11-stage hybrid retrieval: vector search, BM25, RRF fusion, cross-encoder reranking, and MMR diversity for precise recall.
</td>
<td width="25%" align="center">
<h4>⚡ Smart Evolution</h4>
7-decision reconciliation — CREATE, MERGE, SUPERSEDE, SUPPORT, CONTEXTUALIZE, CONTRADICT, or SKIP — makes memories smarter over time.
</td>
</tr>
</table>
📖 **[Memory Pipeline Architecture](docs/PIPELINE.md)** — Technical deep-dive into how ourmem stores, retrieves, and evolves memories.
🔗 **[Memory Sharing Architecture](docs/SHARING.md)** — How memories flow across agents and teams: sharing, provenance, versioning, and cross-space search.
## Feature Overview
| Category | Feature | Details |
|----------|---------|---------|
| **Platforms** | 4 platforms | OpenCode, Claude Code, OpenClaw, MCP Server |
| **Sharing** | Space-based sharing | Personal / Team / Organization with provenance |
| | Provenance tracking | Every shared memory carries full lineage |
| | Quality-gated auto-sharing | Rules fire on memory creation (async, non-blocking) |
| | Vector-enabled shared copies | Shared copies carry source vector embeddings for full search |
| | Idempotent sharing | Re-sharing returns existing copy (no duplicates) |
| | Version tracking | Memories track version counter, shared copies detect staleness via `?check_stale=true` |
| | Re-share stale copies | Refresh outdated shared copies with latest source content and vector |
| | Convenience sharing | One-step cross-user share (`share-to-user`) and bulk share (`share-all-to-user`) with auto-bridging |
| | Organization management | One-step org creation (`org/setup`) and publish (`org/publish`) with auto-share rules |
| | Cross-space search | Search across all accessible spaces at once |
| **Ingestion** | Smart dedup | 7 decisions: CREATE, MERGE, SKIP, SUPERSEDE, SUPPORT, CONTEXTUALIZE, CONTRADICT |
| | Noise filter | Regex + vector prototypes + feedback learning |
| | Admission control | 5-dimension scoring gate (utility, confidence, novelty, recency, type prior) |
| | Dual-stream write | Sync fast path (<50ms) + async LLM extraction |
| | Post-import intelligence | Batch import → async LLM re-extraction + relation discovery |
| | Adaptive import strategy | Auto/atomic/section/document — heuristic content type detection |
| | Content fidelity | Original text preserved, dual-path search (vector + BM25 on source text) |
| | Cross-reconcile | Discover relations between memories via vector similarity |
| | Batch self-dedup | LLM deduplicates facts within same import batch |
| | Privacy protection | `<private>` tag redaction before storage |
| **Retrieval** | 11-stage pipeline | Vector + BM25 → RRF → reranker → decay → importance → MMR diversity |
| | User Profile | Static facts + dynamic context, <100ms |
| | Retrieval trace | Per-stage explainability (input/output/score/duration) |
| **Lifecycle** | Weibull decay | Tier-specific β (Core=0.8, Working=1.0, Peripheral=1.3) |
| | Three-tier promotion | Peripheral ↔ Working ↔ Core with access-based promotion |
| | Auto-forgetting | TTL detection for time-sensitive info ("tomorrow", "next week") |
| **Multi-modal** | File processing | PDF, image OCR, video transcription, code AST chunking |
| | GitHub connector | Real-time webhook sync for code, issues, PRs |
| **Deploy** | Open source | Apache-2.0 |
| | Self-hostable | Single binary, Docker one-liner, ~$5/month |
| | musl static build | Zero-dependency binary for any Linux x86_64 |
| | Object storage | AWS S3 or any S3-compatible storage, with IAM role support |
| | Hosted option | ourmem.ai — nothing to deploy |
## From Isolated Agents to Collective Intelligence
Most AI memory systems trap knowledge in silos. ourmem's three-tier Space architecture enables knowledge flow across agents and teams — with provenance tracking and quality-gated sharing.
> *Research shows collaborative memory reduces redundant work by up to 61% — agents stop re-discovering what their teammates already know.*
> — Collaborative Memory, ICLR 2026
| | Personal | Team | Organization |
|---|----------|------|--------------|
| **Scope** | One user, multiple agents | Multiple users | Company-wide |
| **Example** | Coder + Writer share preferences | Backend team shares arch decisions | Tech standards, security policies |
| **Access** | Owner's agents only | Team members | All org members (read-only) |
**Provenance-tracked sharing** — every shared memory carries its lineage: who shared it, when, and where it came from. Shared copies include the source memory's vector embedding, so they're fully searchable in the target space.
**Quality-gated auto-sharing** — rules filter by importance, category, and tags. Rules fire automatically when new memories are created. Only high-value insights cross space boundaries.
## How It Works
```
┌──────────────────────────────────────────────────────────────────┐
│ Your AI Agent (OpenCode / Claude Code / OpenClaw / Cursor) │
│ │
│ Session Start → auto-recall relevant memories │
│ During Work → keyword detection triggers recall │
│ Session End → auto-capture decisions, preferences, facts │
└───────────────────────────┬──────────────────────────────────────┘
│ REST API (X-API-Key)
▼
┌──────────────────────────────────────────────────────────────────┐
│ ourmem Server │
│ │
│ ┌─ Smart Ingest ─────────────────────────────────────────────┐ │
│ │ Messages → LLM extraction → noise filter → admission │ │
│ │ → 7-decision reconciliation (CREATE / MERGE / SUPERSEDE / │ │
│ │ SUPPORT / CONTEXTUALIZE / CONTRADICT / SKIP) │ │
│ │ → cross-reconcile relations → privacy redaction │ │
│ └────────────────────────────────────────────────────────────┘ │
│ │
│ ┌─ Hybrid Search (11 stages) ────────────────────────────────┐ │
│ │ Vector + BM25 → RRF fusion → cross-encoder reranker │ │
│ │ → Weibull decay boost → importance scoring │ │
│ │ → MMR diversity → parallel cross-space aggregation │ │
│ └────────────────────────────────────────────────────────────┘ │
│ │
│ ┌─ Sharing Engine ───────────────────────────────────────────┐ │
│ │ Personal / Team / Organization spaces │ │
│ │ → provenance tracking → version-based stale detection │ │
│ │ → auto-share rules → one-step share-to-user │ │
│ └────────────────────────────────────────────────────────────┘ │
│ │
│ ┌─ Lifecycle ────────────────────────────────────────────────┐ │
│ │ Weibull decay (Core β=0.8 / Working β=1.0 / Peripheral │ │
│ │ β=1.3) → 3-tier promotion → auto-forgetting TTL │ │
│ └────────────────────────────────────────────────────────────┘ │
└──────────────────────────────────────────────────────────────────┘
```
- **Write once, recall everywhere** — memories persist across sessions, devices, and agents
- **Gets smarter over time** — reconciliation merges, updates, and contradicts memories automatically
- **Share across boundaries** — Personal → Team → Organization knowledge flow with full provenance
- **No manual memory management** — Weibull decay handles lifecycle, auto-share rules handle distribution
## Key Concepts
### API Key = Tenant ID = Your Identity
When you create a tenant, the returned `id` **is** your API Key. They're the same UUID. There is no separate "tenant ID".
```bash
curl -X POST https://api.ourmem.ai/v1/tenants -d '{"name": "alice"}'
# → {"id": "a1b2c3d4-...", "api_key": "a1b2c3d4-...", "status": "active"}
# ↑ same value ↑
```
### API Key vs Space ID
| Concept | What it is | Example | How many |
|---------|-----------|---------|----------|
| **API Key** | Your identity. Goes in `X-API-Key` header. | `a1b2c3d4-...` | 1 per user |
| **Space ID** | A memory storage address. Each is an isolated database. | `personal/a1b2c3d4-...` | Multiple per user |
One API Key owns multiple Spaces:
```
API Key "a1b2c3d4"
│
├── personal/a1b2c3d4 ← auto-created, your private memories
├── team/e5f6g7h8 ← team space you created (you = Admin)
├── team/i9j0k1l2 ← team space you were invited to (you = Member)
└── org/m3n4o5p6 ← organization you joined (you = Reader)
```
### Sharing = Passing Your API Key
To share memories with another user, you pass their API Key as `target_user`:
```bash
# Share all your preferences to user Bob
curl -X POST https://api.ourmem.ai/v1/memories/share-all-to-user \
-H "X-API-Key: your-api-key" \
-d '{"target_user": "bobs-api-key", "filters": {"categories": ["preference"]}}'
```
The system automatically creates a bridging Team Space between you and Bob. No manual space management needed.
## Quick Start
### Agent Install (recommended)
One message to your AI agent. It handles everything — API key, plugin install, config, verification.
**Hosted (ourmem.ai — nothing to deploy):**
| Platform | Copy this to your agent |
|----------|------------------------|
| **OpenClaw** | `Read https://ourmem.ai/SKILL.md and follow the instructions to install and configure ourmem for OpenClaw` |
| **Claude Code** | `Read https://ourmem.ai/SKILL.md and follow the instructions to install and configure ourmem for Claude Code` |
| **OpenCode** | `Read https://ourmem.ai/SKILL.md and follow the instructions to install and configure ourmem for OpenCode` |
| **Cursor / VS Code** | `Read https://ourmem.ai/SKILL.md and follow the instructions to install and configure ourmem as MCP Server` |
**Self-hosted (your own server):**
| Platform | How to install |
|----------|---------------|
| **OpenClaw** | Run `openclaw skills install ourmem`, then tell your agent: `setup ourmem in self-hosted mode` |
| **Claude Code** | `Read https://raw.githubusercontent.com/ourmem/omem/main/skills/ourmem/SKILL.md and install ourmem for Claude Code, self-hosted mode` |
| **OpenCode** | `Read https://raw.githubusercontent.com/ourmem/omem/main/skills/ourmem/SKILL.md and install ourmem for OpenCode, self-hosted mode` |
That's it. Your agent handles the rest.
**Skill Install (alternative):**
If you prefer CLI installation, install the ourmem skill directly:
```bash
npx skills add ourmem/omem --skill ourmem -g
```
This works with 44+ AI agents including Claude Code, OpenCode, Cursor, and more. See [Vercel Skills CLI](https://github.com/vercel-labs/skills) for details.
---
<details>
<summary><b>Manual Install</b> (without agent assistance)</summary>
### 1. Get an API Key
**Hosted:**
```bash
curl -sX POST https://api.ourmem.ai/v1/tenants \
-H "Content-Type: application/json" \
-d '{"name": "my-workspace"}' | jq .
# → {"id": "xxx", "api_key": "xxx", "status": "active"}
```
**Self-deploy:**
```bash
docker run -d -p 8080:8080 -e OMEM_EMBED_PROVIDER=bedrock ghcr.io/ourmem/omem-server:latest
curl -sX POST http://localhost:8080/v1/tenants \
-H "Content-Type: application/json" \
-d '{"name": "my-workspace"}' | jq .
```
Save the returned `api_key` — this reconnects you to the same memory from any machine.
### 2. Install Plugin
**OpenCode:** Add `"plugin": ["@ourmem/opencode"]` to `opencode.json` + configure `plugin_config` with `apiUrl` and `apiKey` in the same file.
**Claude Code:** `/plugin marketplace add ourmem/omem` + set env vars in `~/.claude/settings.json`.
**OpenClaw:** `openclaw plugins install @ourmem/ourmem` + configure `openclaw.json` with apiUrl and apiKey.
**MCP (Cursor / VS Code / Claude Desktop):**
```json
{
"mcpServers": {
"ourmem": {
"command": "npx",
"args": ["-y", "@ourmem/mcp"],
"env": {
"OMEM_API_URL": "https://api.ourmem.ai",
"OMEM_API_KEY": "your-api-key"
}
}
}
}
```
### 3. Verify
```bash
curl -sX POST "$OMEM_API_URL/v1/memories" \
-H "X-API-Key: $OMEM_API_KEY" -H "Content-Type: application/json" \
-d '{"content": "I prefer dark mode", "tags": ["preference"]}'
curl -s "$OMEM_API_URL/v1/memories/search?q=dark+mode" -H "X-API-Key: $OMEM_API_KEY"
```
</details>
## What Your Agent Gets
### Memory Tools
| Tool | Purpose |
|------|---------|
| `memory_store` | Save facts, decisions, preferences with smart dedup |
| `memory_search` | 11-stage hybrid search (vector + BM25 + reranker) |
| `memory_get` | Retrieve a specific memory by ID |
| `memory_update` | Modify content, tags, importance, tier |
| `memory_delete` | Remove a memory |
| `memory_list` | Browse memories with filters and pagination |
| `memory_ingest` | Smart-ingest full conversations (LLM extraction) |
| `memory_profile` | Auto-generated user profile (static facts + dynamic context) |
| `memory_stats` | Analytics: tag distribution, decay curves, relation graphs |
### Sharing Tools
| Tool | Purpose |
|------|---------|
| `space_create` | Create Team or Organization spaces |
| `space_list` | List all accessible spaces |
| `space_add_member` | Invite users to a shared space |
| `memory_share` | Share a memory to any space with provenance |
| `memory_pull` | Pull a shared memory into your personal space |
| `memory_reshare` | Refresh stale shared copies with latest content |
> **Convenience APIs:** `share-to-user` (one-step cross-user share with auto-bridging) and `share-all-to-user` (bulk share). MCP exposes 15 tools + 1 resource. OpenCode/OpenClaw expose 11 tools + 3 hooks.
### Smart Hooks
| Hook | Trigger | What Happens |
|------|---------|--------------|
| **SessionStart** | New session begins | Recent memories + user profile auto-injected into context |
| **KeywordRecall** | Keyword detected mid-session | Relevant memories surfaced without explicit search |
| **SessionEnd** | Session ends | Key decisions, preferences, and facts auto-captured |
| **Compaction** | Context window compressed | Critical memories preserved across compaction boundaries |
## Memory Space
Browse, search, and manage your agent's memories visually at **[ourmem.ai/space](https://ourmem.ai/space)** — see how memories connect, evolve, and decay over time.
## Security & Privacy
| | |
|---|---|
| **Rust Memory Safety** | No garbage collector, no data races. Ownership model guarantees safety at compile time. |
| **Tenant Isolation** | X-API-Key auth with query-level tenant filtering. Every operation verifies ownership. |
| **Privacy Protection** | `<private>` tag redaction strips sensitive content before storage. |
| **Encryption** | HTTPS for all API transit. Server-side encryption at rest on S3. |
| **Admission Control** | 5-dimension scoring gate rejects low-quality data before storage. |
| **Open Source Auditable** | Apache-2.0 licensed. Audit every line, fork it, run your own instance. |
## Self-Deploy
```bash
# Minimal (BM25 search only, no embedding API needed)
docker run -d -p 8080:8080 ghcr.io/ourmem/omem-server:latest
# With Bedrock embedding (recommended, needs AWS credentials)
docker run -d -p 8080:8080 \
-e OMEM_EMBED_PROVIDER=bedrock \
-e AWS_REGION=us-east-1 \
ghcr.io/ourmem/omem-server:latest
# With OpenAI-compatible embedding
docker run -d -p 8080:8080 \
-e OMEM_EMBED_PROVIDER=openai-compatible \
-e OMEM_EMBED_API_KEY=sk-xxx \
ghcr.io/ourmem/omem-server:latest
```
Full deployment guide: [docs/DEPLOY.md](docs/DEPLOY.md)
### Object Storage (Optional)
By default ourmem stores data on local disk. For durability and scalability, configure AWS S3 or any S3-compatible object storage:
```bash
# Add to your environment
OMEM_S3_BUCKET=your-bucket # enables s3:// scheme
AWS_ENDPOINT_URL=https://s3.amazonaws.com
AWS_REGION=us-east-1
# Alternative: OSS-compatible storage
OMEM_OSS_BUCKET=your-bucket # enables oss:// scheme
OSS_ENDPOINT=https://oss-xx-internal.aliyuncs.com
OSS_ACCESS_KEY_ID=your-ak # or use ECS RAM role (auto-discovered)
OSS_ACCESS_KEY_SECRET=your-sk
```
> If both `OMEM_S3_BUCKET` and `OMEM_OSS_BUCKET` are set, OSS takes priority.
## Build from Source
### Two build modes
| Mode | Command | Binary | Bedrock | Runs on |
|------|---------|--------|---------|---------|
| **glibc (full)** | `cargo build --release` | Dynamic linked, ~218MB | ✅ AWS Bedrock | Same glibc version as build host |
| **musl (portable)** | See below | Static linked, ~182MB | ❌ OpenAI-compatible only | **Any Linux x86_64** |
### glibc build (with Bedrock support)
```bash
cargo build --release -p omem-server
# Binary: target/release/omem-server
# Requires: same or newer glibc on target machine
```
### musl static build (portable, zero dependencies)
Single binary that runs on **any Linux x86_64** — no glibc, no libraries, nothing.
```bash
rustup target add x86_64-unknown-linux-musl
RUSTFLAGS="-C target-feature=+crt-static -C relocation-model=static" \
cargo build --release --target x86_64-unknown-linux-musl \
-p omem-server --no-default-features
# Binary: target/x86_64-unknown-linux-musl/release/omem-server
# Statically linked, runs anywhere
```
> **Note:** The musl build uses `--no-default-features` which excludes AWS Bedrock support. Use `OMEM_EMBED_PROVIDER=openai-compatible` (e.g. DashScope, OpenAI) instead. This is because `aws-lc-sys` (AWS crypto library) crashes on musl static linking due to `dlopen(NULL)` incompatibility ([aws-c-cal#213](https://github.com/awslabs/aws-c-cal/issues/213)), and Rust's default `static-pie` output segfaults with musl-gcc ([rust-lang/rust#95926](https://github.com/rust-lang/rust/issues/95926)).
### Transfer to any server
```bash
# Compress
gzip -c target/x86_64-unknown-linux-musl/release/omem-server > omem-server.gz
# Copy to server
scp omem-server.gz user@server:/opt/
# Run (no dependencies needed)
ssh user@server "gunzip /opt/omem-server.gz && chmod +x /opt/omem-server && /opt/omem-server"
```
## API at a Glance
| Method | Endpoint | Description |
|--------|----------|-------------|
| POST | `/v1/tenants` | Create workspace & get API key |
| POST | `/v1/memories` | Store memory or smart-ingest conversation |
| GET | `/v1/memories/search` | 11-stage hybrid search |
| GET | `/v1/memories` | List with filters & pagination |
| GET | `/v1/profile` | Auto-generated user profile |
| POST | `/v1/spaces` | Create shared space |
| POST | `/v1/memories/:id/share` | Share memory to a space |
| POST | `/v1/files` | Upload PDF / image / video / code |
| GET | `/v1/stats` | Analytics & insights |
Full API reference (48+ endpoints): [docs/API.md](docs/API.md)
## Documentation
| Document | Description |
|----------|-------------|
| [docs/API.md](docs/API.md) | Complete REST API reference |
| [docs/PIPELINE.md](docs/PIPELINE.md) | Memory pipeline architecture — storage, retrieval, and plugin integration flows |
| [docs/SHARING.md](docs/SHARING.md) | Memory sharing architecture, flows, and tutorials |
| [docs/DEPLOY.md](docs/DEPLOY.md) | Docker & AWS deployment guide |
| [docs/PLUGINS.md](docs/PLUGINS.md) | Plugin installation for all 4 platforms |
| [docs/TWEETCLAW_OPENCLAW.md](docs/TWEETCLAW_OPENCLAW.md) | OpenClaw workflow for storing TweetClaw X/Twitter research decisions in ourmem |
| [skills/ourmem/SKILL.md](skills/ourmem/SKILL.md) | AI agent onboarding skill |
## License
Apache-2.0
---
<p align="center">
<strong>Shared Memory That Never Forgets.</strong><br/>
<a href="https://ourmem.ai">ourmem.ai</a> · <a href="https://github.com/ourmem/omem">GitHub</a>
</p>
