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Set up BrainLayer — Persistent Memory for AI Agents
pip install brainlayer*Requires Python 3.10+. Installs the CLI, MCP server, and all dependencies.
Point BrainLayer at your Claude Code sessions directory. It will parse JSONL transcripts, chunk content with AST-aware splitting, and generate 1024-dim embeddings.
brainlayer index*First run indexes all sessions. Subsequent runs only process new/changed files.
Add BrainLayer to your Claude Code MCP configuration so it's available in every session.
// ~/.claude/settings.json
{
"mcpServers": {
"brainlayer": {
"command": "brainlayer-mcp"
}
}
}Search your development history using natural language. Results include content, enrichment metadata, and relevance scores.
brainlayer search "how did I implement auth"*Example output: "Found 12 results across 3 projects. Top: JWT middleware in shared/auth.ts (score: 0.89, importance: 8, intent: implementing)"
Run a local LLM to add 10-field metadata to every chunk: summary, tags, importance, intent, and more. Requires Ollama with GLM-4.7-Flash or an MLX-compatible model.
brainlayer enrich*This is optional but dramatically improves search quality. Processing runs locally — no data leaves your machine.
Comprehensive docs with API reference, enrichment fields, search filters, and configuration options.
View BrainLayer Docs