Persistent Memory for AI Agents

Give your agents memory that lasts

Universal memory layer for AI agents. Add persistent, searchable context to any LLM with a single API call.

quickstart.py
from memolayer import MemoryClient client = MemoryClient(api_key="ml-...") # Agent remembers facts from every conversation client.add( messages=[{"role": "user", "content": "I work at Acme Corp, ML team"}], user_id="user_123" ) # Next session — instant recall memories = client.search("Where does the user work?", user_id="user_123") # → [{memory: "Works at Acme Corp, ML team", score: 0.95}]
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Persistent Memory

Agents remember facts across sessions. Auto-extract, deduplicate, and retrieve.

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MCP & SDK

Python SDK, REST API, and MCP server. Works with Claude Code, Cline, LangChain.

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Model-Agnostic

Works with any LLM through OpenAI-compatible interface. Swap models without losing memory.

Launching Q2 2026

Open-source SDK + hosted API. Join the waitlist to get early access and shape the product.

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