Add Persistent Memory to Your AI Agent in 5 Minutes

Most AI agents forget everything the moment their session ends. You can fix that with a single API call. The Agent Memory API gives any AI agent persistent, searchable memory through a REST interface. No vector database. No Redis cluster. No infrastructure to manage. Just HTTP requests. Here's how to wire it into your agent in 5 minutes. The Problem You're building an AI agent — maybe with LangChain, CrewAI, or a custom loop. It works great in a single session. But restart it and... blank slate. Every conversation starts from zero. The usual fixes: Vector databases (Pinecone, Weaviate) — overkill for structured state, expensive, complex setup Redis — fast but ephemeral, no search, another service to manage File storage — no concurrency, no search, doesn't scale What you actually want: a simple key-value store with namespaces, search, and automatic cleanup. What We're Building A Python agent helper that stores and retrieves memories across sessions: from agent_memory import AgentMemory