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Project overview

PentAGI lets autonomous agents plan and execute authorized penetration-testing work inside an isolated Docker environment. It includes more than twenty security tools such as nmap, Metasploit, and sqlmap, and can retain useful findings for later tasks. Cloud and local models are supported; smaller open models benefit from execution monitoring and task planning at the cost of higher token usage.

Project overview

Run an LLM agent that can operate a real browser, terminal, files, keyboard and mouse, screen vision, and Android devices through a small set of local tools. GenericAgent records successful task paths as reusable skills, but you must supply a model API key and complete extra local setup for capabilities such as browser automation, vision, or computer control.

Project overview

Aiden is a Windows-native, local-first autonomous agent that can operate a browser and terminal, invoke tools, run workflows, and persist memory and job state on the user's machine. It supports multiple model providers, subagents, scheduled or external triggers, and long-running work with verification, retries, recovery, and resume behavior. The project is released under AGPL-3.0.

Project overview

Use Hope Agent as a desktop assistant that remembers prior work and keeps long-running goals moving through resumable workflows and multiple agents. The same conversation can move between the native app, a browser, and messaging channels, or run continuously as a server on a NAS or cloud host. macOS is the primary supported environment; Linux and Windows remain less mature, and direct computer control is currently macOS-only.

Project overview

Extract the archive and launch Portable Hermes Agent on Windows without admin rights, a system Python installation, or Docker. Its GUI and CLI can use cloud providers or local models through LM Studio, with tools for automation, custom workflows, runtime tool creation, and optional speech, music, or ComfyUI extensions. It supports Windows 10 and 11 only, and local model use generally requires an NVIDIA GPU with at least 8 GB of VRAM.

Project overview

Bitterbot is a local-first personal AI system with a browser control interface for chat, sessions, memory, skills, and scheduled work. Its dream engine periodically reorganizes stored knowledge, while optional integrations connect messaging channels, a peer-to-peer skills network, and an agent wallet using Base and USDC. Setup is substantial: it requires Node 22, pnpm, several local dependencies, and onboarding for model authentication, embeddings, search, channels, and optional wallet features, making it best suited to users comfortable maintaining an experimental agent environment.

Project overview

Abu Cowork is a local-first desktop AI agent that can plan multi-step work, read and write files, run commands, control a real browser, and create documents or web pages from natural-language requests. Risky actions such as deletion, overwriting, sending, or installation can be placed behind a reviewable plan and explicit approval. Each conversation can use its own model and permission mode. The app also supports installable skills, MCP connectors, schedules, and team messaging channels for broader automation.

Project overview

gptme turns a terminal into an interactive or persistent agent workspace that can inspect and change local projects, run commands, and browse the web or process images when needed. It supports several hosted model providers as well as local llama.cpp models, and can be extended through plugins, skills, MCP tools, ACP editor integration, and templates for scheduled autonomous agents.

Project overview

grok-cli connects a terminal coding agent to xAI’s Grok API, with web and X search, sub-agents, and Telegram control while the CLI keeps running. It offers an interactive terminal UI plus a headless prompt mode. A Grok API key is required, and the community project is not affiliated with or endorsed by xAI.

Project overview

Hermes Agent is designed to retain useful context across sessions by creating skills from experience, searching past conversations, and nudging knowledge to persist. It can run on a small VPS, a GPU cluster, or serverless infrastructure, and Telegram access lets you interact with a cloud instance while it works away from your laptop.

Project overview

OpenClaw is a personal AI assistant that runs on your own devices and connects to common messaging channels such as WhatsApp, Telegram, Slack, and WeChat. It also supports voice and a controllable Canvas across Apple and Android surfaces. The onboarding command guides setup of the gateway, workspace, channels, and skills on macOS, Linux, or Windows.

Project overview

GPT Researcher plans subquestions, gathers evidence in parallel from the web or local documents, tracks sources, and assembles the findings into long reports with citations and export options. Its model, retriever, and MCP data sources can be customized, but typical setups require provider and search API keys. The project is experimental and explicitly does not present its output as academic advice or a recommendation for research papers.

Project overview

Moltis is a self-hosted personal-agent server written in Rust that connects to multiple model providers and stays available through the web, Telegram, Signal, Discord, Teams, and voice. Tool execution can be isolated with Docker, Apple Container, or WASM, while memory, MCP, scheduling, authentication, and an encrypted vault are built in. Release installs run as a single Rust binary on hardware you control.

Project overview

AIlice is a general-purpose autonomous agent that runs from the terminal or a web interface. It can read and analyze documents, conduct focused research, write and execute scripts, perform system-administration tasks, and support voice interaction. Cloud models impose few local hardware demands, but the project says effective local use generally needs a model of at least 70B parameters and two RTX 4090 GPUs, with Ubuntu offering the best compatibility.

Project overview

RepoMaster turns a natural-language task into a workflow that discovers suitable GitHub repositories, understands how to use them, and coordinates specialized agents to execute the work. It offers web and command-line modes for deep search, general assistance, or repository-focused tasks. A model key is required, while deep search also needs Serper and Jina credentials.