41 MCP Tools • 12 Categories • Instant Semantic Search

Documentation

Everything you need to integrate REMBR with your AI tools and build powerful memory-enhanced applications

🚀 Get up and running with REMBR in under 10 minutes

Connect Your Client

🔐 Choose OAuth or API key authentication

Store Your First Memory

💬 Learn through conversation examples

Explore Advanced Features

⚡ Snapshots, analytics, RLM patterns

The production-ready memory layer for AI systems

MCP-Native Architecture

First-class Model Context Protocol support - not just an API wrapper. Works seamlessly with Claude Desktop, VSCode, and any MCP client.

Hybrid Search

Combines semantic embeddings with full-text search for the most relevant results every time.

12 Memory Categories

Organize memories by type: facts, preferences, patterns, decisions, workflows, and more for intelligent context retrieval.

RLM-Optimized

Built for Recursive Learning Machines with snapshots, causal tracing, and temporal queries for debugging agent decisions.

Production-Ready

Multi-tenant SaaS with Row-Level Security, SOC2-ready audit logs, and enterprise-grade infrastructure.

41 MCP Tools

Comprehensive toolset from basic CRUD to advanced analytics, graph visualization, and causal reasoning.

Understand how REMBR works

Complete reference for all 41 MCP Tools

Connect REMBR to your favorite AI tools

RLM, Ralph-RLM, and multi-agent systems