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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.

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Works withDocker

Run score Not tested

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SKILL.md (original)

Review the instructions the agent will receive before you install.

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

Source

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