OpenClaw Universal Memory

Connector-agnostic Postgres + pgvector memory ingestion and retrieval with incremental cursor history.

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 [e-mail] \
  --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 [e-mail] \
  --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 [e-mail] \
  --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.