gbrain-openclaw

Personal knowledge brain for OpenClaw. A single SQLite file with full-text search, vector embeddings, and structured queries — wired into OpenClaw as an MCP server and skill pack.

Based on the GBrain spec by @garrytan. The original design — compiled truth + timeline architecture, thin CLI + fat skills, MCP-native from day one — is Garry's. This repo implements that spec and tailors it for OpenClaw.

What it is

Most knowledge tools fall into two buckets: note apps (Obsidian, Notion) where you write things down, or RAG pipelines where you throw documents at a vector store. GBrain is neither.

It's a compiled knowledge graph: structured pages about people, companies, deals, concepts — each with a compiled truth (always current, rewritten as new info arrives) and a timeline (append-only, never rewritten, the evidence base). It's maintained by AI agents. It's queryable by any MCP client.

brain.db  ← one SQLite file
  pages               compiled_truth + timeline per entity
  page_fts            FTS5 full-text index (auto-synced)
  page_embeddings     Float32 vector embeddings per chunk
  links               cross-references between pages
  tags                tag index
  timeline_entries    structured timeline (queryable by date)
  raw_data            raw API responses (Crustdata, etc.)
  ingest_log          audit trail

Who it's for

GBrain is built around a specific pattern: entities and relationships that accumulate value over time. If your work involves tracking people, companies, deals, or concepts — and you need to recall context across weeks and months, not just within a single conversation — this is for you.

Natural fits:

• Investors — portfolio companies, founders, deal pipeline, LP relationships
• Founders — investor tracking, partner relationships, competitive landscape
• Sales / BD — customer history, follow-up threads, stakeholder maps
• Executives — network management, meeting context, open commitments

The common thread: the core asset is people and relationships, information compounds over time, and you need to retrieve it across sessions.

It also works for research, with a slight mental model shift. Swap out the page types:

papers/attention-is-all-you-need
concepts/transformer-architecture
experiments/ablation-run-42

Compiled truth = your current understanding of this paper or concept. Timeline = notes, replication results, new connections you've drawn. The architecture fits anywhere knowledge accumulates around discrete entities.

What it's not:

• A writing or drafting tool — it's not an editor
• A codebase index — use GStack for that
• A team wiki — designed for a single writer, many readers

Why OpenClaw?

OpenClaw routes conversations across 20+ channels (Telegram, WhatsApp, Slack, iMessage, ...) through a unified AI agent. GBrain gives that agent a durable, structured memory that persists across sessions and channels. Your brain isn't per-conversation — it compounds.

Install

Prerequisites: Bun 1.0+, OpenClaw installed.

# Clone and build
git clone https://github.com/imphillip/gbrain-openclaw
cd gbrain
bun install
bun build --compile --outfile bin/gbrain src/cli.ts

# Put the binary on PATH
sudo cp bin/gbrain /usr/local/bin/gbrain

# Init your brain (defaults to ~/.openclaw/brain.db)
gbrain init

For vector search (optional but recommended):

export OPENAI_API_KEY=sk-...

Wire into OpenClaw

1. Register the MCP server

Add to ~/.openclaw/openclaw.json:

{
  "mcp": {
    "servers": {
      "gbrain": {
        "command": "gbrain",
        "args": ["serve"]
      }
    }
  }
}

This gives every OpenClaw agent access to all brain tools: brain_search, brain_get, brain_put, brain_query, brain_list, brain_stats, brain_timeline, brain_backlinks, and more.

2. Install the skill pack

mkdir -p ~/.openclaw/workspace/skills
cp -r skills/* ~/.openclaw/workspace/skills/

Five skills are included:

3. (Optional) Session auto-ingest hook

Automatically saves conversations to the brain when you issue /new or /reset:

cp -r hooks/gbrain-ingest-session ~/.openclaw/workspace/skills/gbrain-ingest-session

Then add to ~/.openclaw/openclaw.json:

{
  "hooks": {
    "internal": {
      "handlers": [
        {
          "event": "command:new",
          "module": "~/.openclaw/workspace/skills/gbrain-ingest-session/hook.js",
          "export": "default"
        },
        {
          "event": "command:reset",
          "module": "~/.openclaw/workspace/skills/gbrain-ingest-session/hook.js",
          "export": "default"
        }
      ]
    }
  }
}

Usage

CLI

# Write a page
cat page.md | gbrain put people/jane-doe

# Read a page
gbrain get people/jane-doe

# Full-text search
gbrain search "Series A"

# Semantic search (needs OPENAI_API_KEY + at least one embed run)
gbrain query "who is connected to Anthropic?"

# List recent pages
gbrain list --type person --limit 20

# Brain stats
gbrain stats

# Add a timeline entry
gbrain timeline-add people/jane-doe --date 2026-04-06 --summary "Met at YC demo day" --source meeting

# Export to markdown
gbrain export --dir ./export/

# Import from a markdown directory
gbrain import /path/to/notes/

# Generate embeddings
gbrain embed --all         # all pages
gbrain embed --stale       # only pages updated since last embed run

MCP tools (via OpenClaw agents)

Once gbrain serve is registered, any OpenClaw agent can call:

brain_search   — FTS5 keyword search
brain_query    — semantic search (FTS5 + vector)
brain_get      — read a page
brain_put      — write/update a page
brain_list     — list pages with filters
brain_stats    — brain statistics
brain_timeline — get timeline entries
brain_timeline_add — add timeline entry
brain_tags     — list/add/remove tags
brain_backlinks — pages linking to a slug
brain_raw      — read/write raw enrichment data

Via OpenClaw

Once installed, you can talk to your brain naturally:

"What do I know about Acme Corp?" "Ingest this meeting transcript into the brain" "Who in my brain is connected to OpenAI?" "Give me a briefing on active deals" "Add a timeline entry for Jane Doe — we closed the deal"

Page architecture

Pages follow the compiled truth + timeline model:

---
title: Jane Doe
type: person
tags: [founder, yc-alum]
---
# Jane Doe
> CEO of Acme Corp. YC W22. Building AI infrastructure.

## State
[Rewritten whenever new info arrives — always current]

## Open Threads
- [ ] Follow up on Series B timeline

---

## Timeline
- **2026-04-01** | meeting — Demo day. Very impressive product.
- **2025-11-15** | news — Announced $12M seed led by a16z.

The horizontal rule (---) separates compiled truth (above, rewritten) from timeline (below, append-only). Both are stored as separate columns in SQLite, queryable independently.

Slug convention: people/jane-doe, companies/acme-corp, deals/acme-seed, concepts/vector-search

Tech stack

No Postgres. No Pinecone. No Docker. One file.

Development

bun run src/cli.ts <command>                        # dev mode
bun test                                            # run tests
bun build --compile --outfile bin/gbrain src/cli.ts # compile binary

Configuration

Config values stored in the config table:

gbrain call brain_stats '{}'   # check current config

License

MIT

Credits

Spec and architecture — Garry Tan, GBrain.md

Implementation and OpenClaw adaptation — Phillip Wu · 𝕏 · phillip@aclaw.ai

Built for OpenClaw.