Open Brain — The infrastructure layer for your thinking. One database, one AI gateway, one chat channel — any AI plugs in. No middleware, no SaaS.
Open memory & reliability layer for AI agents + independent judging/verification (NACRE judge, caliber-bench meta-benchmark, preregistered criteria) — by Nautilus Platform
Portable semantic memory for AI agents: core engine, TypeScript SDK, framework adapters, MCP server, CLI, and host plugins.
The memory layer for AI-native development - giving AI persistent understanding of your software projects.
Xmem is a India's First open source multi-modal, multi-agentic long‑term memory layer for AI agents.
Shared Memory Storage for Multi-Agent Systems
An open-source, vector-free long-term memory engine for AI agents, achieving SOTA on LoCoMo and LongMemEval with significantly less context.
The memory layer for production AI agents. Python + JS SDKs, 24 framework integrations, MCP server.
Local-first, evidence-aware memory and project continuity for AI coding agents. Checkpoints, context packs and auditable receipts without telemetry.
Give any local LLM a billion-token memory. Open-source, local-first context + memory engine for Ollama and AI agents — runs on your own machine, free. 🧠⚡
Memory for Tutor agents
Dynamic agent memory for LLM agents: 7 neuroscience-inspired layers (working, episodic, semantic, procedural) with FSRS spaced repetition and memory consolidation. Zero-dependency TypeScript library, Model Context Protocol (MCP) server, Vercel AI SDK middleware. Paper: arXiv 2604.23878 · reproduction packages on Zenodo.
local collaboration layer for AI coding agents
Benchmark suite for evaluating retrieval quality and latency of AI agent context systems
Open evaluation harness for AI agent memory systems. Runs LoCoMo and LongMemEval against Synap, Mem0, Zep and Supermemory with pluggable provider adapters.
GoodMem Claude Code plugin — Skills + MCP server for memory infrastructure
MemOS - Universal local-first persistent memory layer for AI agents and LLMs
🧠 Persistent memory for AI agents. SQLite for agent state. Zero cloud dependencies. Local embeddings. MCP-native integration with Claude Desktop/Code, Cursor, Windsurf & more.
dsh-memory-layer：给 DeepSeek Harness 的「记忆层」——本地单文件 SQLite、触发式召回、五条可解释清理规则、工作流链；零服务、零 API、零遥测。A memory layer for DSH: local SQLite, trigger-driven recall, explainable cleanup, workflow chains.
The Open-Source AI Memory Layer: store content, extract atomic memories, search semantically and recall context for AI agents. Self-hostable with an MCP server.
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