MemorySync
Official SDK

Agno + MemorySync

A memory-only db for Agno’s MemoryManager: automatic extraction and injection, server-side similarity search, an async-native twin, and deletes that cannot nuke an account.

Overview

Install agno-memorysync and wire MemoryManager(db=MemorySyncDb()) while sessions stay in your local db — the backend implements every memory method for real and makes every other BaseDb surface raise with the fix in the message, so silent session loss is impossible. Memories extracted by Agno’s native pipeline (update_memory_on_run, agentic memory, image-turn understanding) are kept in MemorySync framework state, one value per memory id, and injected into context on every run; each memory’s text is also sent to fact extraction, so its facts are recallable from every MemorySync surface. get_user_memories(search_content=...) ranks this user’s memories by similarity server-side — Agno’s built-in retrieval is last_n, first_n, or an extra LLM round-trip, and the Mem0 alternative is a toolkit the model must remember to call, with a sync client that blocks async agents and a cookbook that instructs you to comment out the add call after the first run because nothing is idempotent. Here an unchanged memory is recognised and never stored or extracted twice (retries and re-runs converge), an update replaces the facts of the previous version, a delete removes the memory and its facts, reads run under a hard 1.2s budget and fail open, writes fail open with loud logs, failed deletes raise, and the nullary clear_memories() always refuses — per-user wipes are explicit. An AsyncMemorySyncDb twin rides agno’s native AsyncBaseDb path for Agent.arun.

Setup status and requirements

Supported version
agno-memorysync 1.1.0 (PyPI)
Last setup review
2026-08-31
Permissions
A MemorySync API key with read and write scopes.
Limits
Requires agno 2.8+ (Python 3.10+).
Open setup documentation →

Capabilities

Quick Start

from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.memory import MemoryManager
from agno_memorysync import MemorySyncDb
agent = Agent(
db=SqliteDb(db_file="agent.db"), # sessions: local
memory_manager=MemoryManager(db=MemorySyncDb()), # memories: MemorySync
update_memory_on_run=True,
user_id="customer-42",
)
agent.run("I prefer teal dashboards and window seats")
agent.run("Which color should the new chart use?") # remembers

Use Cases

Agno agents that greet returning users with context

Replacing the tool-gated Mem0 toolkit with native automatic memory

Image-turn memories: the model’s understanding persists as recallable facts

Explore More

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