Get started with Open Memory Protocol

This guide walks you through your first end-to-end memory operations using a local Postgres instance as the backend. By the end you will have added a memory, searched it, pulled prompt-ready context, updated it, and deleted it — all through the standard OMP API.

Prerequisites

Python 3.11 or later
Docker (used to run the Postgres + pgvector container in step 1)

Start a Postgres instance

Pull and run the official pgvector image:

docker run --rm -d -p 5432:5432 -e POSTGRES_PASSWORD=postgres pgvector/pgvector:pg16

The container listens on port 5432 and creates a default postgres database. The --rm flag removes the container automatically when you stop it.

Install the SDK

pip install openmem

The core package includes the Postgres adapter and all required dependencies. See Installation for extras that enable other providers.

Set the connection URL

export PG_URL="postgresql://postgres:postgres@localhost:5432/postgres"

The SDK reads PG_URL from the environment when you pass it as the url argument, or you can supply the string directly in code.

Run your first memory operations

Save the following as quickstart.py and run it with python quickstart.py:

import os
from openmem import Memory

url = os.environ.get(
    "PG_URL", "postgresql://postgres:postgres@localhost:5432/postgres"
)
mem = Memory(provider="postgres", url=url)

# Add a memory
m = mem.add(
    content="User prefers pnpm over npm",
    user_id="kek",
    scope="coding/preferences",
    tags=["tooling", "nodejs"],
)
print(f"added: {m.id}")

# Search
results = mem.search(
    query="package manager preferences",
    user_id="kek",
    scope="coding/*",
    limit=5,
)
for r in results:
    print(f"  {r.score:.3f}  {r.memory.content}")

# Get prompt-ready context
ctx = mem.context(
    query="set up a new node project",
    user_id="kek",
    token_budget=500,
)
print(f"\ncontext ({ctx.token_count} tok):\n{ctx.text}")

# Update / supersede
updated = mem.update(
    m.id, content="User prefers bun for new projects", supersedes=[m.id]
)
print(f"\nsuperseded: {updated.id} supersedes={updated.supersedes}")

# Delete
mem.delete(updated.id)
print("deleted.")

Each call goes through the same Memory facade. Swapping the provider= argument is the only change needed to point the same code at a different backend.

Verify provider capabilities

Add this at the end of the script to inspect what the backend supports:

caps = mem.capabilities()
print(f"\nprovider={caps.provider} verbs={caps.verbs}")
if caps.features.graph_queries:
    print("graph queries supported")

The capabilities() call is cached per Memory instance — it only hits the backend once. Use it to degrade gracefully when a feature is not available on your chosen provider.

What’s next

Memory model — understand the fields on a memory record, how scopes work, and what a context block contains.
Switch providers — use the same code against Mem0, Supermemory, or Letta with one line changed.
LLM integration — inject ctx.text into an OpenAI or Anthropic prompt.

Get Started

Core Concepts

Guides

SDK Reference

Get started with Open Memory Protocol

What’s next

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