Infrastructure for
Infinite AI Context
Give your AI agents a persistent long-term memory. Store, recall, and connect information in milliseconds with our Vector-Graph infrastructure.
Built for Agentic Workflow
Everything you need to orchestrate complex context for your autonomous systems.
Vector Graph Cortex
Combines semantic vector search with relational knowledge graphs for 100% accurate recall.
Native MCP Server
Protocol-native implementation. Directly connect LoopMemory to Claude, Cursor, or any MCP client instantly.
$ npx @loopmemory/mcp install
> Authenticating...
> Memory Server Online!
Universally Sync
Real-time synchronization across all your devices and agent instances.
Encrypted Store
Enterprise-grade encryption at rest and in memory. Your data is your own.
ENGINE_SPECS_V2
The infra pipeline for
tomorrow's agents.
Contextual Ingestion
Ingest unstructured data into semantic nodes automatically.
Vector-Graph Mapping
Relational connections mapped alongside vector embeddings.
Low-Latency Recall
Retrieve complex context chains in less than 500ms.
01
Integrate
02
Ingest
03
Recall
// Ingesting new context layer
const memory = await loop.learn({
content: "Project Apollo Specs v2",
tags: ["engineering", "internal"]
});
# Retrieval latency: 242ms
# Entities extracted: 14
# Graph nodes updated: 2