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Awesome GitHub RepositoriesAgent Memory Stores

Persistent storage mechanisms for maintaining state, user preferences, and conversation history across agent sessions.

Distinguishing note: Specifically targets long-term state management for autonomous agents rather than general-purpose application databases.

Explore 51 awesome GitHub repositories matching artificial intelligence & ml · Agent Memory Stores. Refine with filters or upvote what's useful.

Awesome Agent Memory Stores GitHub Repositories

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  • garrytan/gstackgarrytan 的头像

    garrytan/gstack

    110,596在 GitHub 上查看↗

    gstack is an AI agent framework and development workflow system designed to automate the software development lifecycle. It coordinates specialized AI personas to manage tasks across product design, engineering management, and quality assurance, transforming product intent into technical specifications and final releases. The project is distinguished by its deep integration of headless browser automation and semantic code memory. It utilizes a persistent Chromium daemon for web scraping and visual auditing, and implements a searchable knowledge base that logs architectural decisions and repos

    Provides persistent storage for agent plans and decisions to maintain context across different machines and sessions.

    TypeScript
    在 GitHub 上查看↗110,596
  • bytedance/deer-flowbytedance 的头像

    bytedance/deer-flow

    71,310在 GitHub 上查看↗

    Deer-flow is an autonomous agent orchestration platform designed to manage multi-step workflows where AI agents reason, plan, and execute tasks. It functions as a development framework for building agents that utilize various large language models to solve complex problems through structured, sequential, and parallel reasoning. The platform distinguishes itself through a secure, sandboxed execution engine that isolates generated code and system operations from the host environment. This architecture allows agents to safely test and validate solutions within ephemeral containers, ensuring that

    Stores long-term and short-term context to ensure continuity across extended agent execution sessions.

    Pythonagentagenticagentic-framework
    在 GitHub 上查看↗71,310
  • shareai-lab/learn-claude-codeshareAI-lab 的头像

    shareAI-lab/learn-claude-code

    67,975在 GitHub 上查看↗

    This project provides a modular framework for building and orchestrating autonomous AI agents. It functions as an agentic workflow engine that manages the full lifecycle of task execution, including model reasoning, tool invocation, and the integration of results. By utilizing a centralized orchestration platform, the system enables the creation of multi-agent teams that collaborate on complex objectives through structured communication and shared task graphs. The framework distinguishes itself through its focus on persistent, stateful operations and multi-agent coordination. It employs file-

    Persists critical facts, user preferences, and project context across sessions to maintain long-term memory.

    Pythonagentagent-developmentai-agent
    在 GitHub 上查看↗67,975
  • microsoft/ai-agents-for-beginnersmicrosoft 的头像

    microsoft/ai-agents-for-beginners

    67,369在 GitHub 上查看↗

    This project is a structured educational resource and technical guide for designing and implementing autonomous systems using large language models. It provides a comprehensive curriculum and code samples focused on agentic design patterns, autonomous development, and the creation of systems capable of planning and executing multi-step tasks. The resource details the implementation of agentic retrieval-augmented generation, where models autonomously plan and refine data searches. It covers a wide array of orchestrators and design patterns, including metacognitive reflection for self-correctin

    Implements persistent storage mechanisms for maintaining conversation history and user preferences across agent sessions.

    Jupyter Notebookagentic-aiagentic-frameworkagentic-rag
    在 GitHub 上查看↗67,369
  • ruvnet/claude-flowruvnet 的头像

    ruvnet/claude-flow

    61,000在 GitHub 上查看↗

    Claude-flow is an autonomous agent coordination platform and orchestration framework designed for building complex, multi-step workflows powered by large language models. It functions as a TypeScript-based engine that decomposes high-level objectives into executable action sequences, enabling the creation of collaborative agent teams that operate with minimal manual oversight. The platform distinguishes itself through its ability to federate autonomous agents across network boundaries using secure communication channels and identity verification. It integrates a goal-oriented planning engine

    Storing and retrieving contextual knowledge using vector databases to ensure information remains accessible across long-running sessions and tasks.

    TypeScriptagentic-aiagentic-engineeringagentic-framework
    在 GitHub 上查看↗61,000
  • huginn/huginnhuginn 的头像

    huginn/huginn

    49,480在 GitHub 上查看↗

    Huginn is a self-hosted automation platform that functions as an event-driven workflow engine. It allows users to build autonomous agents that monitor web services, scrape data, and execute complex tasks by propagating events through a directed graph. By running on your own server infrastructure, it provides a private environment for orchestrating workflows without relying on third-party automation services. The platform distinguishes itself through a modular, plugin-based architecture that enables the development of custom agents to handle specific data processing needs. Each agent maintains

    Maintains persistent memory objects to track state across multiple execution cycles.

    Rubyagentautomationfeed
    在 GitHub 上查看↗49,480
  • zhayujie/chatgpt-on-wechatzhayujie 的头像

    zhayujie/chatgpt-on-wechat

    45,353在 GitHub 上查看↗

    This project is an autonomous agent framework designed to integrate large language models with popular messaging platforms. It functions as a middleware platform that enables automated, multimodal interactions by decomposing complex user goals into sequential plans, executing them through external tools, and maintaining persistent context across sessions. The framework distinguishes itself through a modular skill architecture and a hybrid memory system. Users can extend system capabilities by installing custom logic modules from community hubs or generating them through natural language. The

    Agent framework stores user preferences, key facts, and conversation summaries in structured files that the system reads and writes automatically to maintain context.

    Pythonaiai-agentchatgpt
    在 GitHub 上查看↗45,353
  • hkuds/nanobotHKUDS 的头像

    HKUDS/nanobot

    44,285在 GitHub 上查看↗

    Nanobot is an orchestration framework designed for building, deploying, and managing autonomous AI agents. It provides a secure runtime environment that supports persistent memory, multi-step workflow management, and tool integration, allowing agents to maintain context and state across long-running tasks. The platform distinguishes itself through a unified model gateway that normalizes requests across diverse local and remote language models, alongside a multi-channel integration layer that connects agents to various messaging platforms. It enforces security through containerized sandboxing

    Stores and versions session history to allow agents to recall information across multiple user interactions.

    Python
    在 GitHub 上查看↗44,285
  • tinyhumansai/openhumantinyhumansai 的头像

    tinyhumansai/openhuman

    32,374在 GitHub 上查看↗

    OpenHuman is an AI application framework for building private intelligence systems and personal AI layers. It provides a system for deploying private AI assistants that execute technical tasks and manage personal knowledge bases. The project features a model-agnostic request proxy that routes AI workloads to different large language models based on requirements for reasoning, speed, or vision. It integrates an OAuth-driven data integrator to synchronize personal information from external services into a local knowledge base composed of hierarchical Markdown summaries. The framework also inclu

    Provides a persistent memory store shared across agents and tools to maintain a consistent user context.

    Rust
    在 GitHub 上查看↗32,374
  • qwibitai/nanoclawqwibitai 的头像

    qwibitai/nanoclaw

    29,956在 GitHub 上查看↗

    Nanoclaw is an LLM agent orchestrator and multi-platform chat gateway designed to deploy and manage isolated AI agents. It provides a containerized runtime that executes agents within sandboxed Linux containers, ensuring filesystem and state isolation through dedicated workspaces and host bind-mounts. The project distinguishes itself through a unified routing pipeline that connects agents to diverse messaging platforms, including WhatsApp, Discord, Slack, Telegram, Signal, and iMessage. It integrates the Model Context Protocol to extend agent capabilities via managed external data and functio

    Implements persistent local memory storage for maintaining user preferences across sessions.

    TypeScriptai-agentsai-assistantclaude-code
    在 GitHub 上查看↗29,956
  • chopratejas/headroomchopratejas 的头像

    chopratejas/headroom

    29,537在 GitHub 上查看↗

    Headroom is an AI gateway proxy and token optimizer designed to reduce the cost and latency of large language model interactions. It functions as an intermediary that intercepts traffic between clients and providers to apply context compression, request routing, and format translation. The system differentiates itself through a Model Context Protocol server implementation that delivers compression and retrieval tools to compatible AI hosts. It employs a content-aware compression pipeline and tiered importance scoring to trim redundant data from logs and tool outputs while preserving essential

    Provides a deduplicated data store shared across agents to maintain consistent project context.

    Pythonagentaianthropic
    在 GitHub 上查看↗29,537
  • supermemoryai/supermemorysupermemoryai 的头像

    supermemoryai/supermemory

    27,334在 GitHub 上查看↗

    Supermemory is an artificial intelligence memory management platform designed to provide autonomous agents with persistent, long-term knowledge bases. It functions as a centralized repository that synchronizes multimodal data, enabling agents to maintain context and historical information across complex, multi-session workflows. By serving as a knowledge graph engine and vector database orchestrator, the platform ensures that information remains accessible and relevant for automated tasks. The system distinguishes itself through its hybrid indexing approach, which combines vector similarity s

    Provides autonomous agents with persistent, long-term knowledge bases to maintain context across complex workflows.

    TypeScriptcloudflare-kvcloudflare-pagescloudflare-workers
    在 GitHub 上查看↗27,334
  • openai/openai-agents-pythonopenai 的头像

    openai/openai-agents-python

    27,191在 GitHub 上查看↗

    This project is a Python framework for building autonomous, event-driven agent systems. It provides a unified runtime for orchestrating multi-agent workflows, managing persistent conversation state, and executing code within secure, isolated sandbox environments. The framework is designed to handle complex task delegation, allowing agents to invoke other agents as tools while maintaining context across multi-turn interactions. The framework distinguishes itself through its deep integration with the Model Context Protocol, enabling agents to connect to external data sources and remote services

    Manages persistent working context across interactions to ensure long-term agent continuity.

    Pythonagentsaiframework
    在 GitHub 上查看↗27,191
  • forem/foremforem 的头像

    forem/forem

    22,726在 GitHub 上查看↗

    Forem is an open-source platform designed for building and managing technical communities. It functions as a social publishing engine that enables members to share long-form content, participate in threaded discussions, and engage through social interactions. The platform provides tools for organizations to maintain branded profiles, host community hackathons, and facilitate collaborative learning through structured educational tracks. Beyond its social features, Forem integrates advanced capabilities for AI agent workflow orchestration and codebase knowledge graphing. It allows developers to

    Distills conversation history into persistent facts to maintain long-term context across agent sessions.

    Rubycommunitydiscussionfeedback
    在 GitHub 上查看↗22,726
  • redis/go-redisredis 的头像

    redis/go-redis

    22,159在 GitHub 上查看↗

    This project is a feature-rich Go client library designed for interacting with Redis. It serves as a comprehensive interface for managing remote data stores, enabling developers to execute standard database commands, handle complex data structures, and perform asynchronous operations within Go applications. The library distinguishes itself through its support for advanced Redis capabilities, including connection pooling, pipelining, and transactional integrity. It provides specialized primitives for managing distributed clusters, including automated topology updates and request routing to sha

    Stores short-term conversation context and long-term user preferences to enable persistent and intelligent agent interactions.

    Gogogolangredis
    在 GitHub 上查看↗22,159
  • joonspk-research/generative_agentsjoonspk-research 的头像

    joonspk-research/generative_agents

    21,565在 GitHub 上查看↗

    Generative Agents is a computational platform for simulating autonomous agents that exhibit human-like social behaviors and decision-making processes. The system functions as a multi-agent simulator where individual participants operate within a virtual environment, driven by large language models to process observations and generate natural language actions. The framework distinguishes itself through a hierarchical memory system that allows agents to store, retrieve, and synthesize past experiences into higher-level insights. This architecture supports the development of complex social dynam

    Provides persistent, structured storage for agent experiences and long-term memory retrieval.

    在 GitHub 上查看↗21,565
  • mastra-ai/mastramastra-ai 的头像

    mastra-ai/mastra

    21,221在 GitHub 上查看↗

    Mastra is an orchestration framework designed for building, deploying, and managing autonomous AI agents and multi-agent systems. It provides a comprehensive suite of primitives for creating resilient AI applications, including durable workflow orchestration, event-driven agent loops, and semantic memory management. By integrating these core components, the platform enables developers to build complex, multi-step processes that can reason about goals and execute tasks without manual intervention. The framework distinguishes itself through its focus on observability and secure, isolated execut

    Stores and retrieves user-specific information across interactions to provide agents with relevant, persistent context.

    TypeScriptagentsaichatbots
    在 GitHub 上查看↗21,221
  • letta-ai/lettaletta-ai 的头像

    letta-ai/letta

    21,168在 GitHub 上查看↗

    Letta is a framework for building, deploying, and managing autonomous AI agents that maintain persistent state across long-term interactions. It provides a comprehensive suite of primitives for defining agents with configurable personas, modular memory blocks, and tool-use capabilities, enabling them to retain user preferences and conversation history over extended sessions. The platform distinguishes itself through its advanced memory management and orchestration capabilities. It allows agents to autonomously update their own memory, perform retrieval-augmented generation, and coordinate com

    Instantiates autonomous agents that maintain persistent memory across sessions to retain user preferences and history.

    Pythonaiai-agentsllm
    在 GitHub 上查看↗21,168
  • topoteretes/cogneetopoteretes 的头像

    topoteretes/cognee

    17,850在 GitHub 上查看↗

    Cognee is an agentic memory management platform designed to provide autonomous agents with long-term semantic recall and structured knowledge. It functions as a framework for building persistent memory systems that connect large language models to graph-based knowledge and vector storage, enabling agents to maintain context across complex tasks and multiple sessions. The platform distinguishes itself through a hybrid approach that combines semantic similarity search with structural graph traversal, allowing for context-aware information retrieval. It features a modular architecture that orche

    Provides long-term semantic recall and structured memory for autonomous agents across complex tasks.

    Pythonaiai-agentsai-memory
    在 GitHub 上查看↗17,850
  • nirdiamant/agents-towards-productionNirDiamant 的头像

    NirDiamant/agents-towards-production

    17,375在 GitHub 上查看↗

    This project is a comprehensive framework for developing, orchestrating, and deploying autonomous agents. It provides a structured environment for building agents that utilize reasoning loops to perform multi-step tasks, manage state through graph-based workflows, and interact with external tools. By mapping unstructured model outputs into typed schemas, the framework ensures reliable integration with downstream application logic. The platform distinguishes itself through a focus on production-grade reliability and security. It incorporates hybrid memory systems that combine vector embeddings

    Manages agent memory by storing conversation history and preferences in hybrid databases.

    Jupyter Notebookagentagent-frameworkagents
    在 GitHub 上查看↗17,375
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探索子标签

  • Distributed Database IntegrationsConnectors for persisting agent memory in distributed SQL database systems. **Distinct from Agent Memory Stores:** Focuses on distributed SQL persistence for agent memory, distinct from general-purpose agent memory stores.
  • Distributed SQL IntegrationsConnectors for persisting agent memory in distributed SQL database systems. **Distinct from Agent Memory Stores:** Focuses on distributed SQL persistence for agent memory, distinct from general-purpose agent memory stores.
  • Document Database IntegrationsConnectors for persisting agent memory in NoSQL document-oriented databases. **Distinct from Agent Memory Stores:** Focuses on document-store persistence for agent memory, distinct from general-purpose agent memory stores.
  • Memory Inspection InterfacesCentralized interfaces for viewing and managing historical execution traces and conversation data. **Distinct from Agent Memory Stores:** Focuses on inspection interfaces, distinct from general memory storage mechanisms.
  • Relational Database IntegrationsConnectors for persisting agent memory in relational database systems. **Distinct from Agent Memory Stores:** Focuses on relational persistence for agent memory, distinct from general-purpose agent memory stores.
  • Weaviate Knowledge Stores1 个子标签Using Weaviate as a persistent vector knowledge backend for AI agents to retrieve context during task execution. **Distinct from Agent Memory Stores:** Distinct from Agent Memory Stores: specifically integrates Weaviate as a vector database for knowledge retrieval, not a general agent memory store.