Persistent Context Across Sessions for Every Agent – Captures everything your agent does during sessions, compresses it with AI, and injects relevant context back into future sessions. Works with Claude Code, OpenClaw, Codex, Gemini, Hermes, Copilot, OpenCode + More
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🌊 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
- agent-memory
- agent-orchestration
- agentic-ai
- agentic-workflow
Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 20% fewer tokens for coding agents, 60-95% fewer tokens for JSON, same answers. Library, proxy, MCP server.
The Memory Layer for AI Agents - Drop-in memory infrastructure for AI agents and apps. Context that persists. Built for production.
Hindsight: Agent Memory That Learns
- agentic-ai
- memory
- agents
- ai-memory
Self-evolving Context Database for AI Agents. Unify Agent Memory, Knowledge RAG and Skills.
- context-database
- agentic-rag
- agent-memory
- self-evolving
Cognee is the open-source AI memory platform for agents. Give your AI agents persistent long-term memory with small models for free
- ai
- cognitive-architecture
- vector-database
- ai-agents
Garry's Opinionated OpenClaw/Hermes Agent Brain
Build Real-Time Knowledge Graphs for AI Agents
Memory and context engine + app that is extremely fast, scalable, and can be run fully locally. The Memory API for the AI era.
- cloudflare-pages
- cloudflare-workers
- drizzle-orm
- tailwindcss
TencentDB Agent Memory is a team-level memory hub for AI Agents — turning conversations, docs, and code into four reusable memory assets (Chat Memory, Skill, LLM-Wiki, Code-Graph) that are governed, shared, and equipped across agents and frameworks.
#1 Persistent memory for AI coding agents based on real-world benchmarks
Beads - A memory upgrade for your coding agent
- agents
- claude-code
- coding
Persistent file-based planning for AI coding agents and long-running tasks. Crash-proof markdown plans, session recovery after /clear and compaction, per-turn re-injection against context rot, deterministic completion gate. Manus-style. Install from npm, the Claude Code plugin marketplace, or npx skills. Codex, Cursor, OpenCode, 60+ agents.
- claude
- claude-code
- claude-skills
- manus
Platform for stateful agents: AI with advanced memory that can learn and self-improve over time.
YC (S26) | Open Computer History | Continuously record your company computer work, map your workflows, help you find work worth automating, and power your agents' context
AI search engine and MCP server for bots and agents. One Rust binary indexes code, docs, logs, JSONL/CSV and PDFs for BM25 full-text, vector and hybrid search, code search without grep, agent memory and RAG. Elasticsearch-compatible API; Corpus Hub serves hundreds of reference memory corpora.
- elasticsearch
- hybrid-search
- search-engine
- vector-search
Build a portrait of your life. Assistants that know you better. Clones that sound more like you.
Memori is agent-native memory infrastructure. A LLM-agnostic layer that turns agent execution and conversation into structured, persistent state for production systems. Built for enterprise, Memori works with the data infrastructure you already run, no rip-and-replace, and deploys across managed cloud, single-tenant cloud, VPC, and on-premises.
Memory layer for AI Agents. Replace complex RAG pipelines with a serverless, single-file memory layer. Give your agents instant retrieval and long-term memory.
Solution for long term memory for agent coding CLIs and to facilitate handoff between different agent vendors
Personal memory across agents
- mcp
- memory
- sandbox
- agent-memory
One portable memory layer for every AI agent: local-first, Markdown-native, user-owned, and self-evolving across apps, tools, and workflows.
- agentic-ai
- ai
- chats
- llm
Self-evolving memory OS for LLM & AI Agents: ultra-persistent memory, hybrid-retrieval, and cross-task skill reuse, with 35.24% token savings and DeepSeek Harness support.