v2.17.0 · MIT
Compound V — a multi-model orchestrator for Claude Code, layered on Superpowers: a deterministic router (Opus for risky work, Sonnet for the mechanical), cross-model review (Claude + Codex), 3 scouts (code · docs · domain), semantic memory, and Epic/Marathon autonomous loop mode. The pill that turns one freelancer into a squad.
v0.2.9 · MIT
AGI 的长期记忆基础设施。让 AI Agent 拥有不可遗忘的自我。跨会话记忆 · 持续学习 · 可审计信任(智能论 v3.2)
— · AGPL-3.0
Self-evolving Context Database for AI Agents. Unify Agent Memory, Knowledge RAG and Skills.
v1.8.1 · MIT
Permission-aware retrieval for AI systems: policy-enforced access to organizational knowledge.
v1.0.0 · MIT
AI skills大全 mcp ai知识库 Agent 全维度 AI 资源百科,DSH插件 收录大模型、智能 Agent、RAG 检索增强、多模态、MLOps、AI 应用工具、AI面试集、Vibe coding 大全、零基础学习路线,持续更新前沿 AI 开源项目,开发者一站式 AI 导航库
v0.54.0 · MIT
OMK — Observe. Measure. Know. Evidence-backed knowledge changes for AI applications.
v1.0.1 · MIT
Page-cited retrieval for embedded docs, datasheets, MISRA, CMSIS, and RTOS references.
v0.1.14 · MIT
Autonomous (auto) mode permission classifier for DeepSeek Harness: a Claude-Code-auto-mode-like classifier over tools/pre-execute and approval/request, a selectable 'auto' permission preset, LLM semantic judge, git checkpointing, agent discipline guidance
v0.20.0 · Apache-2.0
Scaffolding skill + always-on conventions (CLAUDE.md/AGENTS.md) for Quarkus + LangChain4j agentic AI apps: AI services, multi-agent workflows, and RAG. Installable in Claude Code, Codex, Copilot, Cursor, and any Agent Skills-compatible agent.
v0.4.2 · MIT
记忆核心(Memory Eternal):自研的 DeepSeek Harness 记忆插件,不移植任何既有记忆框架——对话结束后自动沉淀知识卡到本地 Markdown Vault(自研去重、自研 CJK 检索、可 git 管理),设置页提供图形化知识库(统计 / 搜索 / 知识图谱 + 侧边栏一键弹窗),Agent 通过 memory_recall 工具按需召回历史上下文。零人工干预。
v1.6.6 · Apache-2.0
Dex is the agent-native analytics engineering toolkit. Point it at your warehouse and your dbt project. It learns the landscape, authors your transformations, and tells you exactly what to fix when the schema drifts. Built for analytics engineers and data engineers who want more out of their coding agent.
v0.1.20 · MIT
Self-evolving memory for DeepSeek Harness (DSH): earned experiences, diary/fact semantic memory, concern tracking, and an append-only audit ledger.
v1.0.2 · MIT
Local and remote knowledge bases for DeepSeek Harness, with scoped recall, controlled write-back, and a Web management console
— · GPL-3.0
🔥 MaxKB is an open-source platform for building enterprise-grade agents. 强大易用的开源企业级智能体平台。
— · Apache-2.0
One portable memory layer for every AI agent: local-first, Markdown-native, user-owned, and self-evolving across apps, tools, and workflows.
— · Apache-2.0
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.
v0.0.0 · Apache-2.0
Caura (formerly MemClaw) — governed shared memory for AI agent fleets. Multi-agent, multi-tenant, MCP-native. Trust tiers, keystone policies, audit trails, knowledge graph, self-improving retrieval. Apache 2.0.
v0.3.0 · Apache-2.0
Your First LLM-Wiki Conversation Knowledge Base
v0.1.0 · AGPL-3.0-only
Your AI agent, fluent in Australian tax. MCP server with cited answers from 34,500+ ATO documents, the income tax and GST Acts and 4,900+ rulings, plus deduction, depreciation, BAS and audit-risk tools that know your tax profile.
— · Apache-2.0
ReMe: Memory Management Kit for Agents - Remember Me, Refine Me.
— · MIT
Context engineering for AI agents. ~80% fewer tokens. Fix tool overload. Skills and memory with in-process BM25 and semantic retrieval. Progressive Disclosure. No vector DB.
v3.21.0 · MIT
The local-first LLM Wiki: open-source knowledge graph builder, RAG knowledge base, and agent memory store. Built on Andrej Karpathy's pattern. An Obsidian alternative for personal knowledge management, AI second brain, and durable Claude Code / Codex / OpenClaw memory.
v4.8.1 · MIT
The agentic harness for AI coding agents — work cycles, bounded RAG context, persistent memory, guardrails, and performance evals.
— · AGPL-3.0
Fast, local-first web content extraction for LLMs. Scrape, crawl, extract structured data — all from Rust. CLI, REST API, and MCP server.