memman is an open-source Python package that provides LLM-supervised persistent memory for AI agents, supporting intent-aware graph recall, retrieval-augmented generation (RAG), and pluggable embeddings. Below are 23 ai & ml apps with similar functionality to memman, matched by what each product actually does — not ranked or scored. Explore each to find the closest fit for your use case.
supermem is an open-source command-line tool that provides persistent AI memory using a four-tier retrieval system, integrating SQLite FTS5, graph, vector, and LLM agent layers. It is designed for AI developers and researchers seeking advanced memory and retrieval capabilities for language models.
getmem-ai is an open-source persistent memory API designed for AI agents and LLM-based applications. It allows developers to store, retrieve, and manage contextual memory, supporting advanced agent workflows and retrieval-augmented generation (RAG). Ideal for AI developers building context-aware systems.
memanto is an open-source companion memory agent designed to help AI agents focus and improve by managing and retaining knowledge. It supports retrieval-augmented generation (RAG) and semantic memory, giving users ownership over learned information.
projectmem is an open-source tool that provides a local-first memory and judgment layer for AI coding agents. It helps agents avoid repeating failed fixes by tracking past actions and outcomes, supporting more efficient and reliable AI-driven coding workflows.
MemBrain is an infrastructure platform that provides persistent, self-evolving memory for AI agents. It enables developers to store, traverse, and recall knowledge graphs and reasoning paths via API or CLI, supporting integration with any LLM through MCP or REST.
Memra is a developer API and CLI tool that offers persistent, privacy-first memory for AI agents and LLM applications. It provides long-term semantic recall, PII masking, and is EU-hosted for compliance. Memra is designed for developers building advanced agentic systems requiring reliable memory infrastructure.
memorylaier is an open-source Python SDK that provides persistent memory infrastructure for AI agents. It enables developers to efficiently store, manage, and retrieve agent memory, supporting advanced AI workflows. The SDK is designed for integration into AI systems and is available under the Apache-2.0 license.
alma-memory is an open-source Python library that provides persistent memory architecture for AI agents. It supports hybrid search, retrieval-augmented generation (RAG), and integrates with Azure and Anthropic models, making it ideal for developers building advanced AI systems.
MemMachine is an open-source memory layer designed for AI agents, allowing them to store, recall, and manage user data and preferences across sessions. It supports multi-agent and multi-session memory, helping developers build more context-aware and personalized AI assistants.
Persistent memory standard for AI agents — local, portable, zero config
Mem Deep Research is an open-source framework that enables AI researchers to orchestrate and manage multiple AI agents for research and automation tasks. It supports integration with large language models and provides extensible tools for building complex agent workflows. The framework is accessible via the command line and is ideal for advanced AI experimentation.
mymem0ry is an open-source personal memory system for AI coding agents, providing offline semantic search, cross-agent handoffs, and zero API key requirements. It is designed for developers building autonomous AI agents that need persistent, shareable memory.
rainman-memory is an open-source library that provides persistent project memory for AI coding agents. It tracks every failure, fix, and decision made by agents, enabling them to recall relevant solutions when similar problems arise. Designed for local use with zero dependencies and no LLM calls, it is ideal for developers building autonomous coding agents.
AutoMem is an open-source infrastructure tool that provides persistent memory for AI agents via MCP and HTTP interfaces. It supports both local and cloud deployments, enabling agents to store and recall structured and semantic data efficiently.
Memanto is an open-source memory agent that provides persistent, local memory and information-theoretic search for AI agents. It integrates with popular agents, runs entirely on the user's machine, and requires no API keys or external vector databases. Designed for developers building advanced AI agent workflows.
yourmemory is an open source Python package that provides persistent memory capabilities for Claude-based and MCP-native AI agents. It features semantic deduplication, Ebbinghaus forgetting curve support, and integrates with SQLite and PostgreSQL. Designed for developers building advanced AI agent workflows.
AgentMem is a universal memory layer for AI agents, offering persistent, searchable, and synced context across frameworks like LangChain, CrewAI, OpenAI, and Claude. It provides an API and CLI for storing, retrieving, and syncing agent memories, helping developers build more context-aware agentic systems.
Mem0 is an infrastructure platform that provides persistent memory for AI agents and applications. It enables context retention across sessions, making it easier for developers to build smarter, more personalized AI systems. Designed for integration via API and SDK.
memosq is an open-source framework that provides persistent, cross-agent memory for AI coding assistants. It leverages semantic search and SQLite to store and retrieve contextual information, enabling more effective and context-aware AI agent collaboration.
m3-memory is an open-source memory framework for AI agents, offering local-first storage, hybrid and vector search, and compatibility with the Model Context Protocol (MCP). It supports both offline and cloud operation, making it suitable for advanced AI agent development.
MEMM is an open-source, local-first AI-native app that creates a persistent, file-based memory for your AI assistants. It helps users and their AI retain and refine knowledge over time, improving context accuracy and reducing redundant explanations. MEMM is cross-platform, privacy-focused, and integrates with MCP for universal AI memory.
Memori is an agent-native memory infrastructure layer for AI systems, turning agent execution and conversations into structured, persistent state. It enables developers to capture, classify, and recall facts, preferences, rules, and summaries from chat interactions, supporting targeted recall and semantic search. Designed for production AI, it helps teams manage and enrich conversational context efficiently.
mempalace is an open-source Python package that enables AI projects to mine and store conversations and project data into a searchable memory palace. It supports retrieval-augmented generation (RAG), vector databases, and works without requiring an API key. Designed for developers building AI systems that need persistent, searchable memory.
