Getting Started

Introduction

agentOrc is a local-first, model-agnostic semantic memory SDK for AI agents.

What is agentOrc?

agentOrc is a lightweight TypeScript SDK that gives multiple AI agents a shared, persistent semantic memory layer. Memory is stored locally with SQLite and searched with sqlite-vec — no servers, no hosted vector database, and no framework lock-in.

You initialize once, then call a small API: remember(), recall(), compress(), forget(), and a few helpers.

What it is not

  • Not an AI agent framework
  • Not an orchestration runtime
  • Not a hosted backend service
  • Not a general-purpose vector database product

It is simply the shared semantic memory layer your agents can all talk to.

Why agentOrc?

  • Local-first — data stays on disk in a SQLite file
  • Multi-agent — concurrent writers are handled for you
  • Model-agnostic — any OpenAI-compatible embedding and chat endpoint
  • Small API — easy to integrate into existing agents

Core ideas

Memories are embedded from content.text, stored with opaque metadata, and retrieved by semantic similarity. Compression can summarize related memories through a separately configured LLM.

Next steps