Mnemosyne – Cognitive memory OS for AI agents (zero LLM calls)
Cognitive Memory OS for AI Agents — persistent, self-improving, multi-agent memory - 28naem-del/mnemosyne
Mnemosyne – Cognitive memory OS for AI agents (zero LLM calls) launched on February 24, 2026 with 5 votes, #1,882 of 16,627 launches that month and more than 75% of that year's launches.
Does a similar job
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Mnemo – local-first AI memory layer for any LLM (Rust, SQLite,petgraph)Jun 2026 · github.com · ▲60Local-first AI memory layer for any LLM. Persistent knowledge graph, entity extraction, semantic retrieval. Works with Ollama, OpenAI, Anthropic, or any OpenAI-compatible backend. - zaydmulani09/mnemo

AgentmemoryMay 2026 · agent-memory.dev · ▲310Persistent memory for Claude Code, Codex & coding agents
Mnemosyne Local hierarchical memory engine for AI agents (MCP Native)Aug 2026 · github.com · ▲10Gomaa — Autonomous Agent Memory OS. Persistent memory system for AI agents with Obsidian vault integration, hybrid RRF search, knowledge graphs, security gates, and MCP server. - M4F-S/gomaa
DeltaMemoryFeb 2026 · deltamemory.com · ▲104Most AI agents forget everything between sessions. We built DeltaMemory to fix that. It's a cognitive memory layer that gives agents persistent recall, automatic fact extraction, and temporal reasoning — via a single SDK call. Key numbers: - 89% accuracy on LoCoMo long-term conversation benchmark - 50ms p50 retrieval latency - 97% cost reduction vs raw token re-processing Open source SDKs, works with any LLM stack. Currently in early access. Happy to answer questions about the architecture, benchmark methodology, or how we handle knowledge graphs.

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