GBrain for BOS
Uses Google Gemini's embedding model for vector search, leveraging the free tier to keep costs low.
Connects as MCP memory to a Hermes Agent, allowing the brain to serve as a memory store for Hermes.
Imports Notion exports into the knowledge brain and manages cost tracking data in a Notion database.
Can be configured to use Supabase as the database backend for scalable storage beyond the embedded PGLite.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@GBrain for BOSWhat did I work on with the Acme account?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
GBrain for BOS
A cost-optimized personal-knowledge brain for running The Builders' Ops Studio.
This is a fork of garrytan/gbrain (MIT, 27.9k★) tuned for a single-operator boutique consultancy at minimum monthly spend.
What's different from upstream
Default cost posture: ~$1–5/mo for active use. Upstream defaults assume enterprise scale.
Conservative search mode + Google Gemini free tier + Haiku synthesis set as the install defaults. Zero new-account cost (Gemini uses your existing Google login). Zero surprise bills.
skills/bos-cost-optimization/— operating manual for keeping spend at floor.Brain Cost Tracker schema documented in this README so the spend is auditable, not implicit.
The engine, hybrid search, MCP server, OAuth admin, and 43 upstream skills are unchanged. They're excellent. Don't fork what works.
Related MCP server: Tyra Advanced Memory MCP Server
Quick start (cost-optimized)
# 1. Install
curl -fsSL https://bun.sh/install | bash
export PATH="$HOME/.bun/bin:$PATH"
bun install -g github.com/cynthiajones34/GBrain
# 2. Set the API keys BEFORE init so the picker auto-selects the cheapest recipe
export GOOGLE_GENERATIVE_AI_API_KEY=<from https://aistudio.google.com/apikey>
export ANTHROPIC_API_KEY=<from https://console.anthropic.com>
# 3. Init with PGLite (zero infra cost) and Gemini free-tier embeddings
gbrain init --pglite --model google:gemini-embedding-001 --embedding-dimensions 768
# 4. Force conservative search mode (smallest token budget)
gbrain config set search.mode conservative
gbrain config set synthesis.expansion false
gbrain config set synthesis.model claude-haiku-4-5
# 5. Wire as MCP memory to your existing Hermes Agent
gbrain serve --http &
gbrain connect https://your-hermes-host/mcp --install
# 6. Import your existing Notion content (free tier covers ~500 pages)
gbrain import ~/notion-export/
# 7. Verify
gbrain doctor
gbrain think "what did I work on with [client name]?"Cost target
Component | Choice | Monthly cost |
Database | PGLite embedded | $0 |
Embeddings | Google Gemini | $0 |
Reranker | (none — hybrid retrieval uses vector + BM25 + RRF) | $0 |
Search mode | conservative (4K token budget) | $0 |
Synthesis | Haiku 4.5 | $0.80–2.50 |
LLM expansion | OFF | $0 |
Total at 1K queries/mo | ~$1–2.50 |
Anything above $5/mo means a knob has drifted. See skills/bos-cost-optimization/SKILL.md.
Tracking spend
All actual spend is logged to the Brain Cost Tracker database in your Notion HQ. Each cost event records service, use case, cost, query count, tokens, model, and an optimization flag. Daily audit cron surfaces drift within 24 hours.
When to upgrade (only after measuring)
conservative→balancedsearch mode: only if recall tests failHaiku → Sonnet synthesis: only if
gbrain thinkanswers hallucinate facts you know are in the brainPGLite → Supabase: only at 50K+ pages or multi-machine access
Never upgrade two knobs at once. You won't know which change caused what.
What's upstream, unchanged
All credit for the engine, search stack, MCP server, OAuth admin, dream cycle, and eval framework goes to Garry Tan and the gbrain contributors. This fork adds cost discipline; it does not replace engineering.
Read skills/RESOLVER.md for skill routing. Read CLAUDE.md if you're Claude Code working on this fork.
License + credit
MIT. Engine and architecture © Garry Tan and gbrain contributors. Cost-optimization layer © Cynthia Jones / The Builders' Ops Studio.
Upstream: github.com/garrytan/gbrain Fork: github.com/cynthiajones34/GBrain
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