---
name: openclaw-universal-memory-a5572cc76703
description: Connector-agnostic Postgres + pgvector memory ingestion and retrieval with incremental cursor history.
---

# OpenClaw Universal Memory

This skill provides a generic memory layer for heterogeneous data:
- canonical entity/chunk schema,
- connector-style ingestion with cursors,
- searchable memory in Postgres.

## Use Cases

- Normalize records from multiple systems into one schema.
- Keep incremental sync history (`cursor` per connector/account).
- Build RAG-ready chunk storage in pgvector.

## Prerequisites

- Postgres with `vector` extension.
- Local package installed: `pip install -e .`.
- Python dependency for DB I/O:
  - `pip install "psycopg[binary]>=3.2"`
- DSN provided via environment variable (`DATABASE_DSN` by default).

## Security Boundaries

- Do not pass raw passwords/tokens in command-line arguments.
- Prefer OS secret store or process environment injection for DSN.
- This skill only reads/writes your configured Postgres database; it does not call external APIs directly.
- Use least-privilege DB credentials (`SELECT/INSERT/UPDATE/DELETE` on `um_*` tables only).
- Review and trust any custom connector before running it.

## Responsible Use Caveat

- Use this only for accounts/data you legitimately control or are authorized to process.
- You are responsible for privacy, retention, and regulatory compliance.
- This project is provided under Apache 2.0 without operational warranty.
- This implementation is mostly AI-generated code with experienced engineer oversight; validate before production use.

## Commands

Store DB credentials once (recommended):

```bash
python skills/openclaw-universal-memory/scripts/run_memory.py \
  --action configure-dsn
```

Initialize schema:

```bash
python skills/openclaw-universal-memory/scripts/run_memory.py \
  --action init-schema \
  --dsn-env DATABASE_DSN
```

Ingest JSON/NDJSON:

```bash
python skills/openclaw-universal-memory/scripts/run_memory.py \
  --action ingest-json \
  --dsn-env DATABASE_DSN \
  --source gmail \
  --account marcos@athanasoulis.net \
  --entity-type email \
  --input /path/to/records.ndjson
```

Ingest from built-in connectors:

```bash
python skills/openclaw-universal-memory/scripts/run_memory.py \
  --action ingest-connector \
  --connector google \
  --account you@example.com \
  --dsn-env DATABASE_DSN \
  --limit 300
```

Validate connector auth/config before ingest:

```bash
python skills/openclaw-universal-memory/scripts/run_memory.py \
  --action validate-connector \
  --connector google \
  --account you@example.com \
  --dsn-env DATABASE_DSN \
  --limit 1
```

Search:

```bash
python skills/openclaw-universal-memory/scripts/run_memory.py \
  --action search \
  --dsn-env DATABASE_DSN \
  --query "Deryk" \
  --limit 20
```

Recent ingest history:

```bash
python skills/openclaw-universal-memory/scripts/run_memory.py \
  --action events \
  --dsn-env DATABASE_DSN \
  --limit 20
```

Doctor check:

```bash
python skills/openclaw-universal-memory/scripts/run_memory.py \
  --action doctor
```

Scheduling reference:
- `docs/SCHEDULING.md` (cron examples, 15-minute default, connector toggles)

## Connector Contract (for custom adapters)

A connector returns normalized records + next cursor:

- `external_id`
- `entity_type`
- `title`
- `body_text`
- `raw_json`
- `meta_json`
- `next_cursor`

This keeps ingestion generic and supports arbitrary source systems.

Starter connector templates:
- `src/openclaw_memory/connectors/templates.py`

Step-by-step setup guide (Gmail/Slack/Asana/iMessage):
- `docs/CONNECTOR_SETUP_WALKTHROUGH.md`


## Community

We welcome connector contributions via PR.
See `docs/CONNECTOR_CONTRIBUTING.md` for required contract, tests, and setup instructions.


---
Source attribution: modbender
Original project: https://github.com/modbender/skill-library-mcp/blob/d9c8fe903b5b4e82237dbe8d0df8567783022e18/data/openclaw-universal-memory/SKILL.md
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2025 skill-library-mcp contributors

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Mega AI Hub resource metadata

Creator / publisher: modbender
Original project: https://github.com/modbender/skill-library-mcp/blob/d9c8fe903b5b4e82237dbe8d0df8567783022e18/data/openclaw-universal-memory/SKILL.md
Attribution basis: Source repository record

Fields of work: Data & Analytics, Development & Engineering, Operations
Roles: Backend Developer, Business Process Analyst, Data Analyst, Data Engineer, ML / AI Engineer
Specialties: Backend, Database
Tools: Pgvector, PostgreSQL
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: 5a0b0597e69ff44df4a7e94024b75f1d086f7cdc6d2cb430e11f5dc1fe363b8c