v1.0.0 · MIT
Verified merchants accepting agentic payments on Lightning/L402/BOLT12/USDT — search, verify, pay.
v1.0.0 · no license
AI-powered news intelligence — 21 tools for personalized monitoring, briefings, and semantic search
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.
— · MIT
Agentic RAG for local and self-hosted document search: hybrid retrieval, reranking and multimodal RAG on embedded LanceDB, with Docling parsing and an MCP server
v5.9.1 · MIT
🥇 The strongest free web search plugin for DeepSeek Harness, and the search bridge for every model without native web access. Free, no signup, no API key. Ask the web or X, get structured JSON evidence. | 🥇 全网最强的 DeepSeek Harness 免费联网搜索插件,免费免注册免 API key。为不能联网的模型补上搜索,问网页或 X,拿回结构化 JSON 证据(搜索、抓取、引用)。
— · MIT
Self-learning vector memory for AI agents — single-file .rvf cognitive container with HNSW search, episodic Reflexion memory, causal graph + Cypher, 9 RL algorithms, Thompson Sampling bandit, 41 MCP tools, hybrid (BM25 + dense) retrieval, GNN attention. 1
v1.6.0 · MIT
The official Pinecone marketplace for Claude Code Plugins
v3.38.20 · MIT
🌊 The original agent meta-harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, RAG integration, and native Claude Code / Codex / Hermes and many more Integrated
v3.38.20 · MIT
🌊 The original agent meta-harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, RAG integration, and native Claude Code / Codex / Hermes and many more Integrated
v2026.04.26.2 · MIT
Open-source deep research for AI agents: 40 channels, 10+ Chinese sources.
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.
— · 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.
— · no license
Open-source LLM knowledge platform: turn raw documents into a queryable RAG, an autonomous reasoning agent, and a self-maintaining Wiki.
— · Apache-2.0
Open-source persistent memory for AI agent pipelines (LangGraph, CrewAI, AutoGen) and Claude. REST API + knowledge graph + autonomous consolidation.
— · MIT
A lightweight, rollbackable, and visual Long-Term Memory Server for MCP Agents. Say goodbye to Vector RAG and amnesia. Empower your AI with persistent, graph-like structured memory across any model, session, or tool. Drop-in replacement for OpenClaw.
— · Apache-2.0
Agent Skill for Baidu Netdisk (百度网盘) — upload, download, transfer, share, search files via natural language. Works with Claude Code, Cursor, Codex, Gemini CLI, OpenClaw.
— · no license
No description yet.
v1.6.2 · MIT
Persistent project knowledge graph for coding agents. MCP server with semantic search, in-process embeddings, and web explorer.
— · no license
专利侵权分析系统 —— 输入专利公开号,产出竞品侵权分析报告;同时打包成 skill,可被任意 agent(codex,claude code 等) 调用。
— · no license
CoexistAI is a modular, developer-friendly research assistant framework . It enables you to build, search, summarize, and automate research workflows using LLMs, web search, Reddit, YouTube, and mapping tools—all with simple MCP tool calls or API calls or Python functions.