Discoverable MCP Tools • Scoped Memory • Hybrid 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

Supports bounded snapshots, scoped relationship graphs, and temporal queries for debugging stored agent context.

Production-Ready

Tenant, project and user authorisation with selected database RLS boundaries and scoped audit records.

MCP Tool Suite

Credential-aware MCP tools for memory CRUD, scoped search, contexts, snapshots, graphs, and statistics.

Understand how REMBR works

Reference for the current MCP tool suite

Connect REMBR to your favorite AI tools

RLM, Ralph-RLM, and multi-agent systems