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Local-first persistent memory layer for AI agents. Provides hybrid search (FTS5 keyword + vector embeddings) over 223K+ knowledge chunks via MCP. Tools: brain_s
Local-first persistent memory layer for AI agents. Provides hybrid search (FTS5 keyword + vector embeddings) over 223K+ knowledge chunks via MCP. Tools: brain_search, brain_store, brain_entity, brain_subscribe. Features pub/sub with stable agent identity, delivery tracking, and Claude --channels integration. SQLite + BrainBar Swift daemon on Unix socket.
Your AI has amnesia. BrainLayer fixes that.
PyPI CI License MCP Tests Website
Every architecture decision, every debugging session, every preference you've expressed — gone between sessions. You repeat yourself constantly. Your agent rediscovers bugs it already fixed.
BrainLayer gives any MCP-compatible AI agent persistent memory across conversations. One SQLite file. No cloud. No Docker. Just pip install.
"What approach did I use for auth last month?" → brain_search
"Remember this decision for later" → brain_store
"What was I working on yesterday?" → brain_recall
"Ingest this meeting transcript" → brain_digest
"What do we know about this person?" → brain_get_person
pip install brainlayer
Add to your MCP config (~/.claude.json for Claude Code):
{
"mcpServers": {
"brainlayer": {
"command": "brainlayer-mcp"
}
}
}
That's it. Your agent now remembers everything.
Cursor (MCP settings):
{
"mcpServers": {
"brainlayer": {
"command": "brainlayer-mcp"
}
}
}
Zed (settings.json):
{
"context_servers": {
"brainlayer": {
"command": { "path": "brainlayer-mcp" }
}
}
}
VS Code (.vscode/mcp.json):
{
"servers": {
"brainlayer": {
"command": "brainlayer-mcp"
}
}
}
Every tool includes ToolAnnotations so agents know which calls are safe to run without confirmation.
| Tool | Type | What it does |
|---|---|---|
brain_search |
read | Semantic + keyword hybrid search across all memories. Lifecycle-aware. |
brain_store |
write | Persist decisions, learnings, mistakes. Auto-importance scoring. Per-agent scoping via agent_id. |
brain_recall |
read | Proactive retrieval — session context, summaries, recent work. |
brain_resume |
read | Recover recent PreCompact checkpoints for explicit session restoration. |
brain_tags |
read | Browse tags and discover what's in memory without a query. |
brain_digest |
write | Ingest raw content — entity extraction, relations, action items. |
brain_entity |
read | Look up knowledge graph entities — type, relations, evidence. |
brain_expand |
read | Get a chunk with N surrounding chunks for full context. |
brain_update |
write | Update importance, tags, or archive existing memories. |
brain_get_person |
read | Person lookup — entity details, interactions, preferences. |
brain_enrich |
write | Run LLM enrichment — Gemini, Groq, or local MLX/Ollama. |
brain_supersede |
destructive | Replace old memory with new. Safety gate on personal data. |
brain_archive |
destructive | Soft-delete with timestamp. Recoverable via direct lookup. |
All 14 legacy brainlayer_* tool names still work as aliases.
graph LR
A["Claude Code / Cursor / Zed"] -->|MCP| B["BrainLayer<br/>13 tools"]
B --> C["Hybrid Search<br/>vector + FTS5"]
C --> D["SQLite + sqlite-vec<br/>single .db file"]
B --> KG["Knowledge Graph<br/>entities + relations"]
KG --> D
E["JSONL conversations"] --> W["Real-time Watcher<br/>~1s latency"]
W --> D
I["BrainBar UI<br/>NSStatusItem + NSPopover"] -->|UDS /tmp/brainbar.sock| BB["BrainBarDaemon<br/>MCP + brain bus"]
BB -->|MCP socket protocol| B
Everything runs locally. Cloud enrichment (Gemini/Groq) and Axiom telemetry are optional.
| Layer | Implementation |
|---|---|
| Storage | SQLite + sqlite-vec, WAL mode, single .db file |
| Embeddings | bge-large-en-v1.5 (1024 dims, CPU/MPS) |
| Search | Vector similarity + FTS5, merged with Reciprocal Rank Fusion |
| Watcher | Real-time JSONL indexing (~1s), 4-layer content filters, offset-persistent |
| Enrichment | 10 metadata fields per chunk — Groq, Gemini, MLX, or Ollama |
| Knowledge Graph | Entities, relations, co-occurrence extraction, person lookup |
| BrainLayer | Mem0 | Zep/Graphiti | Letta | |
|---|---|---|---|---|
| MCP tools | 13 | 1 | 1 | 0 |
| Local-first | SQLite | Cloud-first | Cloud-only | Docker+PG |
| Zero infra | pip install |
API key | API key | Docker |
| Real-time indexing | ~1s | No | No | No |
| Knowledge lifecycle | Supersede/archive | Auto-dedup | No | No |
| Open source | Apache 2.0 | Apache 2.0 | Source-available | Apache 2.0 |
Optional native Swift menu bar companion split into two launchd-managed processes:
flowchart LR
UI["BrainBar<br/>LSUIElement UI"] -->|"watch-brain-bus + commands<br/>/tmp/brainbar.sock"| D["BrainBarDaemon<br/>headless MCP server"]
D -->|"single writer queue + reads"| DB["SQLite WAL<br/>~/.local/share/brainlayer/brainlayer.db"]
D -->|"helper subprocess IPC"| H["Hybrid search helper"]
BrainBarDaemon owns the MCP server, /tmp/brainbar.sock, the single-writer path, the watch-brain-bus stream, and helper subprocess lifecycle. BrainBar owns only the NSStatusItem, transient NSPopover, SwiftUI surfaces, hotkey routing, and a reconnecting socket subscriber. Killing the UI does not stop the daemon socket.
bash brain-bar/build-app.sh # Build, sign, install LaunchAgent
The build script builds both BrainBar and BrainBarDaemon, embeds both binaries in BrainBar.app, then installs com.brainlayer.brainbar.plist and com.brainlayer.brainbar-daemon.plist with ProcessType=Interactive. It refuses non-canonical checkouts and dirty trees by default (#265) and stamps each bundle with GitCommit, GitDescribe, and BuildTimeUTC in Info.plist (#264) so a stale install is diagnosable in seconds.
Background producers run with BRAINLAYER_ARBITRATED=1 and append writes to ~/.brainlayer/queue/; com.brainlayer.drain.plist drains that queue every 500ms as the single writer. Trigram FTS maintenance is explicit via brainlayer repair-fts and the weekly com.brainlayer.repair-fts.plist, not synchronous startup work. See docs/arbitration.md.
Two-week stability sprint behind the next presentation. Every line below traces to a merged PR.
Search recall & dedup
brain_search (#242).content_hash index dropped — was blocking re-enrichment writes (#245).brain_store queue fallback so BrainBar can persist when the daemon is mid-restart (#261).BrainBar reliability & UX
initialize handshake preserved under backpressure (#247).onAppear timer reset — kills CPU pegging when the graph tab is idle (#249).Phase B preventive infra (2026-05-01) — one canonical artifact per environment
/post-merge-deploy-check skill + initial canonical-deploy-registry.json (orchestrator#60) cross-checks GitHub merge metadata, the registry, and the deployed app's Info.plist so a merged PR cannot be declared shipped while the local bundle still points at the wrong build.Test gates — pre-push gate is mandatory before any push to main
scripts/run_tests.sh orchestrator unifies Python + Swift + isolation test runs (#256).Security
MCPRouter tools exposed via BrainBar now ship ToolAnnotations (cyberMaster H1) (#253).In flight (2026-05-02 reliability sprint) — PR #251
NSPanel (BrainBarDashboardPanelController) instead of MenuBarExtra(.window).chunks_fts_trigram) with a startup-safety guard: synchronous backfill is skipped when the desynced trigram table exceeds 10K chunks, so BrainBar never blocks the live ~360K-chunk database before /tmp/brainbar.sock opens.AgentActivityMonitor for live CLI presence on the dashboard./tmp/brainbar.sock is explicitly preserved (brain_subscribe, brain_unsubscribe, notifications/claude/channel) — only search/store handlers move to the Python MCP path.Phase 5 ship wave (2026-05-17) — ingest hygiene + KG regression fix
recursive_mcp_output_reason now detects BrainLayer-MCP-unavailable diagnostics and PreCompact checkpoint payloads, rejecting them at the watcher / drain / store ingestion heads so tooling failures do not become durable memory. The hybrid reranker demotes (not removes) any chunk tagged with precompact/quarantine signals so explicit include_checkpoints callers still see them. Pre-push gate: 1995 passed, 9 skipped, 75 deselected, 1 xfailed. A dry-run-first scripts/quarantine_noise.py is available for back-filling existing infra noise — live DB mutation requires explicit --apply.brain_digest silently skipped Gemini entity extraction because process_chunk passed use_llm=llm_caller is not None and the MCP/CLI path never sets llm_caller. Non-seed person entities were never materialized into kg_entities / kg_entity_chunks. The 2026-04-06 entity-recall recurrence root-caused to this code path. RED-first regression test (test_digest_content_persists_llm_people_entities_for_lookup) now guards the fix.com.brainlayer.enrichment was silently unloaded since 2026-05-15 11:50 IDT (no entity extraction running). Bootstrapped back on 2026-05-17 against the 56K-chunk backfill; throttled by Gemini 503s on flex tier but actively draining (verified via launchctl list | grep enrichment returning a live PID).June 2026 search & KG hardening (#433–#445)
chunk_origin on every processed chunk; a backfill pass covers existing unknowns, making provenance queryable across the full corpus.brain_search applies Maximal Marginal Relevance post-retrieval dedup automatically; pass mmr=false to opt out.| Source | Indexer |
|---|---|
| Claude Code | brainlayer index (JSONL from ~/.claude/projects/) |
| Claude Desktop | brainlayer index --source desktop |
| Codex CLI | brainlayer ingest-codex |
brainlayer index --source whatsapp |
|
| YouTube | brainlayer index --source youtube |
| Markdown | brainlayer index --source markdown |
| Manual | brain_store MCP tool |
| Real-time | brainlayer watch LaunchAgent (~1s, 4-layer filters) |
Each chunk gets 10 structured metadata fields from a local or cloud LLM:
| Field | Example |
|---|---|
summary |
"Debugging Telegram bot message drops under load" |
tags |
"telegram, debugging, performance" |
importance |
8 (architectural decision) vs 2 (directory listing) |
intent |
debugging, designing, implementing, deciding |
primary_symbols |
"TelegramBot, handleMessage, grammy" |
epistemic_level |
hypothesis, substantiated, validated |
brainlayer enrich # Run enrichment on new chunks
BRAINLAYER_ENRICH_BACKEND=groq brainlayer enrich # Force Groq
brainlayer init # Interactive setup wizard
brainlayer index # Batch index conversations
brainlayer watch # Real-time watcher (persistent, ~1s)
brainlayer search "query" # Semantic + keyword search
brainlayer enrich # LLM enrichment on new chunks
brainlayer stats # Database statistics
brainlayer brain-export # Brain graph JSON for visualization
brainlayer export-obsidian # Export to Obsidian vault
brainlayer dashboard # Interactive TUI
pip install -e ".[dev]"
git config core.hooksPath .githooks # install repo pre-push hook once per clone
pytest tests/ # 1,848 Python tests
pytest tests/ -m "not integration" # Unit tests only (fast)
ruff check src/ && ruff format src/ # Lint + format
# BrainBar: 54 Swift tests via Xcode
| Variable | Default | Description |
|---|---|---|
BRAINLAYER_DB |
~/.local/share/brainlayer/brainlayer.db |
Database file path |
BRAINLAYER_ENRICH_BACKEND |
auto-detect | Enrichment backend (groq, gemini, mlx, ollama) |
GROQ_API_KEY |
(unset) | Groq API key for cloud enrichment |
AXIOM_TOKEN |
(unset) | Axiom telemetry token (optional) |
BRAINLAYER_ENRICH_RATE |
5.0 |
Requests per second (5.0 = 300 RPM, AI Pro supports 500+) |
BRAINLAYER_SANITIZE_EXTRA_NAMES |
(empty) | Names to redact from indexed content |
See full configuration reference for all options.
pip install "brainlayer[brain]" # Brain graph visualization + FAISS
pip install "brainlayer[cloud]" # Gemini Batch API enrichment
pip install "brainlayer[youtube]" # YouTube transcript indexing
pip install "brainlayer[ast]" # AST-aware code chunking (tree-sitter)
pip install "brainlayer[kg]" # GliNER entity extraction (209M params)
pip install "brainlayer[telemetry]" # Axiom observability
pip install "brainlayer[dev]" # Development: pytest, ruff
Contributions welcome! See CONTRIBUTING.md for dev setup, testing, and PR guidelines.
Apache 2.0 — see LICENSE.
BrainLayer is part of the Golems MCP agent ecosystem:
Originally developed as "Zikaron" (Hebrew: memory). Extracted into a standalone project because every developer deserves persistent AI memory.
Run in your terminal:
claude mcp add brainlayer -- npx CSA PROJECT - FZCO © 2026 IFZA Business Park, DDP, Premises Number 31174 - 001
Security
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