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Agent Memory

Tools and platforms providing long-term memory, knowledge persistence, and context management for AI agents — including cross-session memory, knowledge graphs, and personalization

89 projects

Graphify

114.0k · Python
Active A+

AI coding assistant skill that turns any folder of code, docs, papers, images, or videos into a queryable knowledge graph. Works with Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot CLI, and more.

memorypythonagent +2
  • · Knowledge graph generation — automatically converts code, docs, PDFs, images, and videos into queryable knowledge graphs
  • · Multi-platform AI assistant integration — supports Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot and 20+ platforms
  • · Interactive visualization — generates browsable graph.html with node clicking, filtering, and search

Claude Mem

93.0k · JavaScript
Active A+

A Claude Code plugin that automatically captures coding session context, compresses it with AI, and injects relevant context back into future sessions for persistent memory.

codingmemoryagent +2
  • · Cross-session persistent memory - Automatically captures tool observations and generates semantic summaries, injecting relevant context into new sessions
  • · Progressive disclosure - Layered memory retrieval with token cost visibility for precise control over injected context volume
  • · Skill-based search - Query project history via mem-search skill with semantic project context retrieval

MiroFish

71.9k · Python
Active A+

Multi-agent swarm intelligence engine that extracts seed information from the real world, constructs a high-fidelity parallel digital world with thousands of agents, and predicts future trajectories through social evolution simulations.

multi-agentswarm-intelligenceknowledge-graph +3
  • · Multi-agent swarm simulation — thousands of agents with independent personalities and long-term memory freely interact
  • · GraphRAG knowledge graph — automatically constructs a high-fidelity parallel digital world from seed materials
  • · Dynamic memory — continuously updates individual and collective memory during simulation

Headroom

68.6k · Python
Active A+

Context compression layer that compresses tool outputs, logs, files, and RAG chunks before they reach the LLM, saving 60-95% of tokens while preserving answer quality. Available as library, proxy, or MCP server.

token-compressionoptimizationmcp +2
  • · Compress everything before LLM receives it, reducing 60-95% of tokens
  • · Three usage modes: library, proxy, and one-command agent wrapping
  • · Built-in MCP server with cross-agent shared memory

Embedchain

64.6k · Python
Active A+

Embedchain is a universal memory layer for AI agents, enabling quick integration of diverse data sources into LLMs for context-aware AI applications.

memoryragembeddings +2
  • · Universal memory layer — quickly integrates diverse data sources (web, PDFs, YouTube, Notion) into LLMs for context
  • · Vectorized storage — auto-chunks, embeds, and stores data in vector databases with semantic retrieval support
  • · Multi-LLM backend support — compatible with OpenAI, Cohere, Ollama and other LLM and embedding models

Mem0

64.6k · Python
Active A+

Mem0 is a long-term memory layer for AI agents, supporting cross-session memory management and personalized context retrieval.

memoryragpersonalization +1
  • · Multi-level memory — seamlessly manages user, session, and agent memory states with adaptive personalization
  • · Single-pass ADD extraction — one LLM call extracts memories with no UPDATE/DELETE, memories accumulate only
  • · Entity linking — entities extracted, embedded, and linked across memories for retrieval boosting

Context7

61.5k · TypeScript
Active A+

Context7 is Upstash's context-engineering toolkit for agents, helping applications manage long context windows, retrieval injection, and history compression.

contextmemoryretrieval +1
  • · Real-time documentation retrieval — pulls latest version-specific library docs and code examples via MCP or CLI, injected directly into LLM context
  • · Dual-mode integration — supports CLI + Skills (ctx7 commands) and MCP Server, compatible with Cursor/Claude Code/OpenCode and other major agents
  • · Library version matching — automatically resolves library names and versions to fetch precise, version-appropriate docs

MemPalace

58.8k · Python
Active A+

MemPalace is an open-source AI memory system providing a persistent long-term memory layer for AI agents, with ChromaDB vector storage and MCP protocol integration.

memorylong-term-memorychromadb +2
  • · Verbatim storage & semantic search — conversation history stored as-is, retrieved via semantic search without summarization or paraphrasing
  • · Palace-style indexing — organizes memory as Wings (people/projects) → Rooms (topics) → Drawers (verbatim content)
  • · Local-first zero API — core retrieval requires no API key, cloud, or LLM, uses ChromaDB as default local vector store

Codebase Memory MCP

41.9k · C
Active A+

High-performance code intelligence MCP server that indexes codebases into a persistent knowledge graph, supporting 66 languages with sub-millisecond queries and 99% fewer tokens.

mcpknowledge-graphcode-analysis +2
  • · Extreme indexing speed: Linux kernel (28M LOC) indexed in 3 minutes via RAM-first pipeline
  • · 159 languages supported through vendored tree-sitter grammars in a single binary
  • · Hybrid LSP semantic type resolution for Python, TypeScript, PHP, C#, Go, C, and C++

ChatTTS

39.8k · Python
Stale B

A generative speech model for daily dialogue, providing AI agents with natural and fluent voice synthesis with fine-grained prosody control.

voicepythonagent +1
  • · Conversational TTS — Optimized for dialogue scenarios like LLM assistants with natural expressive synthesis
  • · Fine-grained prosody control — Predict and control laughter, pauses, interjections and subtle prosodic features
  • · Multi-speaker support — Sample random speaker timbre, supports multi-character dialogue scenarios

Khoj

37.0k · Python
Normal A

Khoj is a self-hostable AI second brain that answers questions from the web or your docs, builds custom agents, schedules automations, and performs deep research.

second-brainragself-hosted +2
  • · Multi-LLM support — Switch between local and cloud LLMs including llama3, qwen, gemma, mistral, gpt, claude, gemini, deepseek
  • · Multi-format document retrieval — Get answers from PDFs, Markdown, Word, Notion, org-mode, images and more
  • · Custom agent creation — Build custom agents with custom knowledge, persona, chat model and tools

OpenViking

35.2k · Python
Active A

OpenViking is an open-source context database from Volcengine that unifies management of agent memory, resources, and skills through a filesystem paradigm, enabling hierarchical context delivery and self-evolution.

memorycontext-managementagent +2
  • · Filesystem paradigm management — organize agent memory, resources, and skills in a filesystem structure, eliminating fragmented storage
  • · L0/L1/L2 three-tier context loading — on-demand hierarchical context loading to significantly reduce token consumption and costs
  • · Directory recursive retrieval — combines directory positioning with semantic search for recursive and precise context acquisition

QwenPaw

34.8k · Python
Active A

Personal AI assistant from the AgentScope team with an Agent OS architecture, three-layer memory, kernel-level sandboxing, and one instance serving DingTalk, WeChat, Telegram and more.

personal-assistantmulti-channelmemory +2
  • · Three-layer memory — live working context, full verbatim history, and a ReMe-powered self-evolving knowledge base that becomes searchable Markdown memory
  • · Local or cloud, runs free — bundled QwenPaw-Flash models (2B/4B/9B) need no API key, and Ollama plus 14+ cloud providers also work
  • · Security built in — kernel-level Sandbox, Tool Guard, File Guard, Skill Scanner, and Access Policy block dangerous commands before they run

Graphiti

30.5k · Python
Active A+

Graphiti is a temporal knowledge-graph engine for agent memory, helping systems continuously accumulate long-term context.

memoryknowledge-graphrag +1
  • · Temporal fact management — Each fact has a validity window; old facts are invalidated, not deleted. Query what's true now or at any point in time
  • · Provenance & lineage tracking — Every entity and relationship traces back to raw data episodes, full lineage from derived fact to source
  • · Hybrid retrieval — Combines semantic embeddings, keyword BM25, and graph traversal for low-latency high-precision queries without LLM summarization

Cognee

30.4k · Python
Active A+

A knowledge engine for AI agent memory that builds knowledge graphs and memory layers in 6 lines of code, supporting graph databases, vector stores, and more for knowledge extraction and retrieval.

agent-memoryknowledge-graphvector-store +2
  • · Build knowledge graphs and memory layers in 6 lines of code
  • · Core API: remember, recall, forget, improve operations
  • · Session memory and permanent knowledge graph dual-mode

Supermemory

29.2k · TypeScript
Active A+

An extremely fast and scalable memory engine for the AI era. Provides a unified Memory API for AI applications with large-scale knowledge storage and efficient retrieval.

memoryknowledge-basevector-search +2
  • · Conversational Memory Extraction — Automatically extracts facts from conversations handling temporal changes and contradictions
  • · User Profile Building — Auto-maintains user preferences, projects, and recent activity context summaries
  • · Hybrid Search — RAG and memory search unified, retrieving knowledge docs and personalized context together

AgentMemory

27.9k · TypeScript
Active A

A persistent memory system for AI coding agents, designed around real-world benchmarks to preserve context across sessions.

memorycoding-agentpersistent-memory +1
  • · Cross-session persistent memory — AI coding agents preserve context across sessions, no re-explanation needed
  • · MCP protocol support — 53 MCP tools compatible with Claude Code, Copilot, Cursor and other agents
  • · Auto hook system — 12 automatic hooks save and retrieve memories during agent operations

Beads

26.8k · Go
Active A

A memory upgrade for coding agents. Provides persistent contextual memory for Claude Code, Codex, and other coding agents to improve long-task consistency.

coding-agentmemorycontext +2
  • · Dolt-powered versioned SQL database — cell-level merge, native branching and remote sync
  • · Dependency-aware task graph — replaces Markdown TODOs with graph structure supporting blocks/related/parent-child relationships
  • · Agent-optimized output — JSON output format, dependency tracking and auto-ready task detection

Kotaemon

25.7k · Python
Normal A

Kotaemon is an open-source RAG-based tool for chatting with your documents, featuring a clean chat interface and support for multiple LLM and embedding model backends.

ragdocument-qapdf +2
  • · Hybrid RAG pipeline — combines full-text and vector retrieval with re-ranking for best retrieval quality
  • · Multimodal document QA — supports PDF, HTML, XLSX formats with figure and table extraction from documents
  • · Advanced citations with document preview — relevance-scored citations with in-browser PDF viewer and highlight support

TencentDB Agent Memory

25.7k · TypeScript
Active A

TencentDB Agent Memory delivers fully local long-term memory for AI agents via a 4-tier progressive pipeline, with zero external API dependencies, vector search, and embedding storage.

agent-memorylong-term-memorylocal-first +3
  • · Symbolic short-term memory using Mermaid canvas to compress verbose logs into compact tokens
  • · Layered long-term memory with 4-tier semantic pyramid (L0 Conversation → L3 Persona)
  • · Up to 61.38% token reduction and 51.52% pass rate improvement with OpenClaw

pgvector

22.9k · C
Active A

Open-source vector similarity search extension for PostgreSQL, enabling native vector storage and ANN retrieval in relational databases, a foundational component for building agent memory and RAG systems.

vector-databasepostgresqlsimilarity-search +2
  • · PostgreSQL native extension — Store and query vectors directly in relational database, no extra infrastructure
  • · Multiple distance metrics — L2, cosine distance, inner product, L1, Hamming, and Jaccard distance
  • · Exact and approximate search — HNSW and IVFFlat indexes for ANN approximate nearest neighbor search

MaxKB

22.7k · Python
Active A+

MaxKB is an open-source knowledge base Q&A and agent building platform powered by LLMs, with vector retrieval, workflow orchestration, and multi-model support out of the box.

knowledge-baseragchatbot +3
  • · RAG Pipeline — Document upload and online crawling with automatic splitting and vectorization to reduce hallucinations
  • · Agentic Workflow — Powerful workflow engine, function library and MCP tool-use for complex business scenarios
  • · Zero-code Integration — Seamlessly integrate into third-party business systems for smart Q&A capabilities

Hindsight

22.2k · Python
Active A+

Hindsight is an agent memory system that learns autonomously, supporting memory retention, recall, and reflection to give AI agents persistent experiential memory.

memoryagentlearning +2
  • · Agent memory system focused on learning rather than just remembering, with retain/recall/reflect operations
  • · State-of-the-art performance on LongMemEval benchmark, independently reproduced by Virginia Tech and Washington Post
  • · LLM Wrapper for 2-line integration swapping your current LLM client with Hindsight memory-enabled client

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