Peekaboo
✨macOS GUI automation tool powered by AI vision — captures screenshots, detects UI elements via multi-provider LLMs, and executes clicks/types/scrolls through natural language or scripted workflows
macOS GUI automation tool powered by AI vision — captures screenshots, detects UI elements via multi-provider LLMs, and executes clicks/types/scrolls through natural language or scripted workflows
A cross-platform terminal aggregator with built-in AI Agent panels for Claude Code and OpenAI Codex, featuring multi-workspace management, Git worktree isolation, session persistence, and token cost monitoring.
Next-gen multi-agent orchestration desktop app that unifies Claude Code, Gemini CLI, Codex CLI and other CLI tools into collaborative AI agent squads
A fully on-device voice AI assistant for macOS Apple Silicon, integrating STT, LLM, TTS, VLM, RAG, and system control with zero cloud dependency.
A macOS-native AI coding terminal built on Ghostty, featuring vertical tabs, notification system, and embedded browser for multi-agent workflows.
Open-source AI coding agent supporting 75+ LLM providers with terminal/desktop/IDE interfaces, Plan/Build dual-agent modes, designed for code comprehension, feature development, and code modification.
A Rust-based local-first AI assistant with persistent memory, autonomous task execution, and kernel-level sandbox security, supporting multiple LLM providers and interfaces.
The official inference framework for 1-bit Large Language Models by Microsoft. It features optimized kernels for lossless, high-speed inference on CPUs and GPUs, drastically reducing energy consumption and enabling 100B+ parameter models to run on local consumer hardware.
A shell and coding agent integrated into Claude Desktop app, empowering chat applications to code, build, and run directly on your local machine.
An open-source multimodal AI Agent stack developed by ByteDance, comprising the general Agent TARS framework and the UI-TARS Desktop client. It enables natural language control of computers, browsers, and terminals via Vision-Language Models.
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