AI Memory Systems

Correction-first persistent memory for AI agents. MCP server + SDK + CLI. Compounds across sessions.

Correction-first persistent memory for AI agents. MCP server + SDK + CLI. Compounds across sessions.

Complete ETCLOVG framework for AI Agent workflows - DAG+FSM orchestration, Ebbinghaus memory, discipline routing, skill evolution, trace system, governance. 80+ tests, zero deps, 7/7 layers.

🤖 Desktop AI Assistant with Local Model Support - OpenAI SDK compatible agent with memory system, file operations, web search, and modern UI. Supports vLLM, Ollama, Qwen, Llama, and more.

A practical AI agents handbook covering agent systems, agentic workflows, LangGraph, MCP/A2A, context engineering, agent memory, evaluation, observability, and multi-agent architecture. Current trend focus: Gemini Interactions API and managed agents, emerging agent runtimes, and production AI workflow patterns.

A curated list of AI Agent evolution, memory systems, multi-agent architectures, and self-improvement projects. | evomap.ai

Alice is a voice-first desktop AI assistant application built with Vue.js, Vite, and Electron. Advanced memory system, function calling, MCP support, optional fully local use, and more.

M.I.L.E.S, a GPT-4-Turbo voice assistant, self-adapts its prompts and AI model, can play any Spotify song, adjusts system and Spotify volume, performs calculations, browses the web and internet, searches global weather, delivers date and time, autonomously chooses and retains long-term memories. Available for macOS and Windows.

The best-benchmarked open-source memory system for AI coding assistants

Aetox harness: a local-first Windows AI environment - model, skills, team and memory as one system. Two doors - an Assistant that adapts to your work and drives a real browser; and a Developer that names each weakness before writing, checks the project's security, runs the project's tests before saying done, and remembers what this project decided.

Framework for AI agents to build and maintain a digital brain through Obsidian wiki | Memory System for Agents

Independently authored prompt templates for AI coding agents — system prompts, tool prompts, agent delegation, memory management, and multi-agent coordination. Informed by studying Claude Code.

Comprehensive MCP server exposing dozens of capabilities to AI agents: multi-provider LLM delegation, browser automation, document processing, vector ops, and cognitive memory systems

Give your AI agent a brain that remembers. Local memory system for Claude Code — 100% private, GPU-accelerated, zero cloud dependency.

A memory system using mem0 for AI applications. Enables long-term memory for AI agents as a drop-in MCP server.

Stop re-explaining yourself to AI. MARM offers persistent memory, cross-agent context sharing, write queues, swarm-ready presets, and compaction for clean recall. Includes a live web dashboard for managing memories, logs, and sessions. MCP connects over HTTP & STDIO and works with major LLMs like Claude, Codex, Grok, Gemini, and other models.

AI Agent Orchestrator with Skills System - Give AI Agents superpowers: memory search, code graph queries, agent-to-agent messaging. Manage Claude Code, Codex, Grok Build or any AI Agent from one dashboard. Move Agents between computers and locations

Open survey and evidence map for AI agent evolution, self-evolving agents, memory, skills, harnesses, benchmarks, and agent-swarm systems.

🪼 A personal AI assistant that lives in Telegram — every topic is its own isolated Claude Code agent with layered persistent memory and proactive cron heartbeats. Open skeleton of a real, running system.

Project memory system for AI coding assistants (Claude Code, Cursor, Codex): session logs, project wiki, rules, TODOs, and handoff.

Synapse is a local-first personal memory operating system designed for AI agents. It provides durable, typed, and highly reliable long-term memory using only local SQLite — giving agents the ability to remember, update, and reason over facts across sessions with full user control.

🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, federation, vector RAG integration, and native Claude Code / Codex / Hermes and many more Integrated

AINL helps turn AI from "a smart conversation" into "a structured worker." It is designed for teams building AI workflows that need multiple steps, state and memory, tool use, repeatable execution, validation and control, and lower dependence on long prompt loops. AINL is a compact, graph-canonical, AI-native programming system for (READ: README)

Give your AI a real, persistent memory. The open-source system plus templates that turn an Obsidian vault into your AI's working memory. No vector database, just markdown.