Search results for "claw"
Most advanced AI coworker
Open-source sandboxes for code execution, browser use, and AI agents.
Security scanner for GitHub repos, Agent Skills, Plugins, and MCP servers. 18 scanners. Zero dependencies.
See your agent think. Real-time observability dashboard for OpenClaw AI agents.
OpenViking is an open-source context database designed specifically for AI Agents(such as openclaw). OpenViking unifies the management of context (memory, resources, and skills) that Agents need throu
Python Deep Agent framework built on top of Pydantic-AI, designed to help you quickly build production-grade autonomous AI agents with planning, filesystem operations, subagent delegation, skills, and
44 plug-and-play skills for OpenClaw — self-modifying AI agent with cron scheduling, security guardrails, persistent memory, knowledge graphs, and MCP health monitoring. Your agent teaches itself new
The agent that grows with you
A Markdown-first memory system, a standalone library for any AI agent. Inspired by OpenClaw.
Accelerating Long Context LLM Inference with Accuracy-Preserving Context Optimization in SGLang, vLLM, llama.cpp, OpenClaw, RAG, and Agentic AI.
An open-source AI assistant framework with skills and agent architecture
AI memory OS for LLM and Agent systems(moltbot,clawdbot,openclaw), enabling persistent Skill memory for cross-task skill reuse and evolution.
A more beautiful and easier-to-use alternative to OpenClaw. It features a nicer Web UI, built-in IM support, and a sandboxed runtime for improved safety. Under the hood, it is powered by a Claude Code
PowerMem: Your AI-Powered Long-Term Memory — Accurate, Agile, Affordable. Also friendly support for the OpenClaw Memory Plugin.
aivectormemory 是一款基于 Model Context Protocol (MCP) 开发的OpenClaw、OpenCode、ClaudeCodeAI记忆管理工具。它专门为 Claude、OpenCode、Cursor 和 主流IDE 编程工具设计，通过向量数据库技术解决 AI 在不同对话会话中「健忘」的问题。aivectormemory: A lightweight MCP Se
Open-source multi-agent AI assistant powered by LangGraph, FastAPI & Next.js — 16+ agents, Human-in-the-Loop, MCP integration, voice TTS, RAG, 500+ metrics, 6 languages.
Ultra-Lightweight, Pure Python Multimodal Agent.
PraisonAI 🦞 — Hire a 24/7 AI Workforce. Stop writing boilerplate and start shipping autonomous agents that research, plan, code, and execute tasks. Deployed in 5 lines of code with built-in memory, R
PinchBench is a benchmarking system for evaluating LLM models as OpenClaw coding agents. Made with 🦀 by the humans at https://kilo.ai
基于 AI Agent 工作流的修仙世界模拟器，旨在还原智能、开放的仙侠世界。| An open-source Cultivation World Simulator using Agentic Workflow to create a dynamic, emerging Xianxia world.
Curated directory of terminal-native AI coding agents and the harnesses that orchestrate them. Covers open-source tools (Pi, OpenCode, Aider, Goose), platform agents (Claude Code, Codex, Gemini CLI),
OpenClawProBench is a live-first benchmark harness for evaluating LLM agents in the OpenClaw runtime with deterministic grading and repeated-trial reliability.
Claw-Eval is an evaluation harness for evaluating LLM as agents. All tasks verified by humans.
AgenticX is a unified, production-ready multi-agent platform — Python SDK + CLI (agx) + Studio server + Machi desktop app. Features Meta-Agent orchestration, 15+ LLM providers, MCP Hub, hierarchical m
Automate ChatGPT registration and extract OAuth access_token and refresh_token with email handling, Sentinel bypass, and PKCE capture
🏛️ Hermes Gate — Terminal TUI for managing remote Hermes Agent sessions with auto-reconnect, detach support, and zero config
Self-evolving agent: grows skill tree from 3.3K-line seed, achieving full system control with 6x less token consumption
🦀 The first autonomous hackathon agent stop assisting and start competing (🏆 Hackathon Champion Project).
The API layer for AI agents. Dashboard + 22K APIs + 18 Direct Call providers. MCP native.
Connect any LLM to OpenClaw — production-tested middleware for Qwen3-235B and beyond
Self-evolving AI agent framework with 5-layer safety gatekeeper. Agents observe failures, propose fixes, and safely apply them. Built on HKUDS/nanobot.
Enable peer-to-peer collaboration between AI agents with human supervision for complex task coordination and decision-making.