Build a self-updating agent memory graph with GBrain

Build a self-updating agent memory graph with GBrain

Use GBrain to give OpenClaw or Hermes-style agents a local knowledge brain with markdown ingestion, entity links, hybrid search, scheduled consolidation, and MCP access.

Prerequisites

GBrain CLI, Bun/Node-compatible runtime, PGLite or Postgres with pgvector, markdown knowledge base, optional MCP server deployment

Installation

Requirements and caveats from upstream:

• gbrain init --pglite # 2 seconds; no server, no Docker
• Run bun run test for the fast loop, bun run verify for the pre-push gate, bun run ci:local to run the full Docker-backed CI stack locally. Detailed test discipline in CONTRIBUTING.md.

Basic usage or getting-started notes:

• Built by the President and CEO of Y Combinator to run his actual AI agents. The production brain behind his OpenClaw and Hermes deployments: 17,888 pages, 4,383 people, 723 companies, 21 cron jobs running autonomo...

• New in v0.35.7 — Temporal trajectory + founder scorecard. Author typed metric assertions in the ## Facts fence (mrr=50000, arr=2000000, team_size=12) and gbrain stores them as first-class typed columns. gbrain eva...

• GBrain runs in three shapes. Pick the one that matches how you use AI agents today.

• Source: https://github.com/garrytan/gbrain

• Extracted from upstream docs: https://raw.githubusercontent.com/garrytan/gbrain/HEAD/README.md

Documentation

• https://github.com/garrytan/gbrain/blob/master/llms.txt

Source

• Agent Skill Exchange