Your AI has amnesia. BrainLayer fixes that.

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.

{
  "mcpServers": {
    "brainlayer": {
      "command": "brainlayer-mcp"
    }
  }
}

{
  "context_servers": {
    "brainlayer": {
      "command": { "path": "brainlayer-mcp" }
    }
  }
}

{
  "servers": {
    "brainlayer": {
      "command": "brainlayer-mcp"
    }
  }
}

Every tool includes ToolAnnotations so agents know which calls are safe to run without confirmation.

All 14 legacy brainlayer_* tool names still work as aliases.

graph LR
    A["Claude Code / Cursor / Zed"] -->|MCP| B["BrainLayer<br/>12 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<br/>macOS menu bar"] -->|Unix socket| B

Everything runs locally. Cloud enrichment (Gemini/Groq) and Axiom telemetry are optional.

Optional 209KB native Swift menu bar app. Quick capture (F4), live dashboard, knowledge graph viewer — all over a Unix socket. Auto-restarts after quit via LaunchAgent.

bash brain-bar/build-app.sh    # Build, sign, install LaunchAgent

Requires the BrainLayer MCP server.

Each chunk gets 10 structured metadata fields from a local or cloud LLM:

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]"
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

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:

• BrainLayer — Persistent memory (this repo)
• VoiceLayer — Voice I/O for AI agents
• cmuxLayer — Terminal orchestration for AI agents

Originally developed as "Zikaron" (Hebrew: memory). Extracted into a standalone project because every developer deserves persistent AI memory.