GBrain Alternative

GBrain is great.
But it needs a database.

GBrain (garrytan/gbrain) validates the idea of persistent AI memory. 2,500+ stars on GitHub. But it requires Supabase, pgvector, bun, and an OpenAI API key before you can use it. Brainfile is the same idea — without the infrastructure tax.

What GBrain is, and what Brainfile is

GBrain: an open-source persistent-memory system for Claude Code (garrytan/gbrain, 2,500+ GitHub stars). It stores memories as vector embeddings in a Supabase/pgvector database, retrieved automatically via semantic search, and needs an OpenAI API key for the embeddings.

Brainfile: a library of maintained CLAUDE.md configurations — structured role and project context that Claude Code reads automatically from your project root, updated as Claude evolves.

Both aim to give Claude standing context instead of re-explaining yourself every session. GBrain does it with a database and semantic retrieval; Brainfile does it with a plain markdown file Claude reads on its own, no infrastructure required.

Using GBrain vs. using Brainfile

GBrain workflow
  1. 1Create a Supabase account and project
  2. 2Enable the pgvector extension in Supabase
  3. 3Run the SQL schema migration in Supabase
  4. 4Install bun (JavaScript runtime)
  5. 5Clone the gbrain repository
  6. 6Set OPENAI_API_KEY environment variable
  7. 7Set SUPABASE_URL and SUPABASE_KEY env vars
  8. 8Run bun install to install dependencies
  9. 9Add memories via CLI commands
  10. 10Budget ongoing costs for Supabase and OpenAI API usage
⏱ 2–3 hours setup · plus ongoing Supabase + OpenAI API infrastructure costs
Brainfile workflow
  1. 1Download your profession's configuration
  2. 2Customize the [PLACEHOLDER] sections with your info
  3. 3Save it as CLAUDE.md in your project root
  4. 4Run claude in your project — it works immediately
✓ 15–30 minutes · No additional infrastructure · Works with your existing Claude subscription

Head-to-head: Brainfile vs. GBrain

FeatureGBrainBrainfile
AI model support OpenAI only (GPT-4, embeddings API required) Claude, ChatGPT, Gemini, Cursor — any AI tool
Infrastructure required Supabase + pgvector + bun + Node.js runtime None — just your existing Claude subscription
Claude Code integration Indirect — requires extra tooling to export to CLAUDE.md format Native — configurations are CLAUDE.md files, work immediately
Setup time 2–3 hours (database setup, CLI config, API keys) 15–30 minutes (customize placeholders, save as CLAUDE.md)
Monthly infrastructure cost Meaningful ongoing spend — Supabase free tier exhausted quickly, plus OpenAI API usage No additional cost — included in your subscription
Profession-specific configurations Generic memory storage — you write all the context yourself 15 expert-crafted configurations (Developer, Founder, Trader, Marketer, and 11 more)
Long-term maintenance You maintain the infrastructure, keep dependencies updated We maintain and update configurations monthly as Claude evolves
Works offline / local Requires database connection (Supabase is cloud-only) CLAUDE.md files work completely offline — no external dependencies
Licensing MIT (open source, no ongoing support) Commercial — active development + support + monthly updates
Context approach Vector embeddings (semantic search over stored memories) Structured markdown (explicit, transparent, fully controllable)

Honest answer: when to use each

Use GBrain if…

You're a developer who enjoys building and maintaining your own infrastructure, already have OpenAI API access, and want semantic memory search across thousands of stored memories with full control over every part of the system.

Use Brainfile if…

You want to spend time on your actual work, not setting up databases. You use Claude Code and want a CLAUDE.md that works immediately, with expert-crafted configurations you can customize in 30 minutes and updates as Claude evolves.

Use both if…

GBrain's vector memory and Brainfile's CLAUDE.md solve different problems — semantic recall across ad-hoc notes versus a maintained role-context file Claude reads automatically every session. If you already run GBrain's infrastructure, a CLAUDE.md costs nothing extra to add alongside it. Start with the 3 free configurations and see whether the persistent half is worth it.

Vector embeddings vs. structured markdown

GBrain uses vector embeddings — it stores memories as semantic chunks and retrieves relevant ones automatically based on your query. This is powerful for unstructured data at scale.

Brainfile uses structured markdown — everything is explicit, transparent, and fully in your control. You read it, you edit it, you know exactly what Claude sees. No black-box retrieval, no wondering why it did not include something.

GBrain
  • ± Automatically retrieves relevant memories
  • You can't see exactly what's included in context
  • Requires a database + embedding API to be running
  • Good for unstructured notes; overkill for role context
  • You write all the memories yourself from scratch
Brainfile
  • + Full transparency — you see exactly what Claude reads
  • + Works offline — no external services required
  • + Native CLAUDE.md format — Claude Code reads it automatically
  • + Expert-crafted structure — not a blank slate
  • + Easy to edit, version-control, share with team
Get started in 15 minutes

No database.
No infrastructure.
Just better Claude.

15 production-ready CLAUDE.md configurations. Updated monthly. Works with your existing Claude subscription.

Start free trial — 30 days, no card 3 free samples first

30-day money-back guarantee · Instant access · Cancel anytime

Not ready to buy? Stay in the loop.

AI context engineering tips and new configuration releases. Free.

No spam. Unsubscribe anytime.