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Documentation Index

Fetch the complete documentation index at: https://docs.openmem.blog/llms.txt

Use this file to discover all available pages before exploring further.

Open Memory Protocol (OMP) gives your AI application one consistent API for storing, searching, and retrieving memory — regardless of which backend powers it. Write your code once against Memory.add(), Memory.search(), and Memory.context(), then swap between Postgres, Mem0, Supermemory, or Letta with a single line change.

Quick Start

Run your first memory operation in under 5 minutes using the Postgres backend.

Installation

Install the openmem package with the extras for your chosen provider.

Core Concepts

Understand memories, scopes, providers, and context blocks.

API Reference

Full HTTP endpoint reference with request and response schemas.

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How it works

OMP sits between your application and any memory backend. You call the same Python methods (or HTTP routes) regardless of which provider you choose. The SDK automatically detects whether a provider speaks OMP natively and selects the right adapter for you.
1

Install the SDK

pip install openmem
2

Connect to a provider

from openmem import Memory

mem = Memory(provider="postgres", url="postgresql://localhost/omp")
3

Add and search memories

mem.add(content="user prefers pnpm over npm", user_id="u1", scope="coding/preferences")

results = mem.search("package manager", user_id="u1")
print(results[0].memory.content)
4

Inject context into LLM prompts

ctx = mem.context("set up a new node project", user_id="u1", token_budget=500)
# ctx.text is ready to prepend to your system prompt

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Supported providers

ProviderStatus
Postgres + pgvectorReady
Mem0Available
SupermemoryAvailable
LettaAvailable
Any native OMP serverPassthrough

Switch providers

Learn how to change backends with zero application code changes.

Async usage

Use AsyncMemory for non-blocking memory operations in async apps.

LLM integration

Inject ranked, citation-tagged memory into any LLM prompt.

HTTP server

Run omp-server to expose OMP over HTTP for any language or framework.