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blogmemory

Memanto Python client: agent memory in ten lines

At a glance

Memanto 0.2.28 ships a Python client so any agent gets persistent typed memory with one import: remember()/recall()/answer()/extract() plus point-in-time recall_as_of and recall_changed_since. Cloud (free tier) or on-prem Docker+Ollama; no vector store to provision. Loop pattern: recall before your LLM call, extract only the user’s turn after—connects to Claude Code/Cursor/Codex via memanto connect. This workflow is listed under memory, Python, coding-agents, agent-loop.

Agents / tools
Memanto, Python, Claude Code, Cursor, Codex

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Prompt excerpt

from memanto import Memanto; m=Memanto(agent_id='support-bot'); m.remember('Ship Thursdays never Fridays', type='decision'); print(m.answer('When do we ship?')['answer'])

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