FIRERPA Android

Escrcpy is an open-source graphical interface for displaying and controlling Android devices through the scrcpy engine. It provides an embedded mirror with screen-fitting and orientation handling, configurable mappings for touch, joystick, swipe, scrolling, and automation, simultaneous control of multiple devices with broadcast input, batch screenshots and APK installation, and a draggable control bar for device operations. It also supports wireless ADB connections with LAN discovery and Gnirehtet reverse tethering, visual step-by-step automation with screen-image recognition, global shortcuts, and an MCP-based AI assistant with multi-model chat. Released packages are available for manual installation, with macOS installation through Homebrew; advanced features from the private EscrcpyX extension are paid, and the project states that updates are irregular.

ARTEMIS is an open-source Google tool for natural-language Android automation and testing. It drives real phones or emulators through end-to-end workflows, generates test plans, captures screenshots and logs, profiles performance, and produces structured reports. Its element-locating system combines accessibility hierarchies and OCR with visual-model and coordinate fallbacks for custom interfaces. ARTEMIS provides a CLI, web visual console, Python SDK, and native Model Context Protocol (MCP) server for connecting Android devices to AI coding assistants such as Antigravity, Claude Code, Codex, and Windsurf. Its Flash profile uses a reactive observe-and-act loop with compressed history, while the Pro profile uses planning, pre-execution checks, action bursts, incident recovery, checkpoint verification, and optional final reports. The project also includes an accessibility helper for reading screen layouts and can fall back to UIAutomator2. It is distributed under the Apache License 2.0; the repository reports 99%+ completion on Google Research's AndroidWorld benchmark.

Renfield is a self-hosted, voice-first AI household assistant built with FastAPI, React, and Ollama. It uses Raspberry Pi Zero 2 W voice satellites with ReSpeaker HATs for local wake-word detection, Whisper speech recognition, Piper text-to-speech, and SpeechBrain speaker recognition. The system can track room presence through BLE scanning, voice recognition, and web authentication, and integrates with Home Assistant and DLNA for multi-room control. Its ReAct agent chains tools through 10 MCP servers covering weather, web search, news, calendars, Jellyfin, DLNA, n8n workflows, Home Assistant, Paperless, email, and related services. It also provides conversational long-term memory with contradiction detection, a knowledge graph with validated entity-relation triples, and a RAG knowledge base that combines dense pgvector embeddings with BM25 full-text search using reciprocal-rank fusion. Documents can be uploaded from formats including PDF, DOCX, PPTX, XLSX, HTML, Markdown, and TXT, with Tesseract or EasyOCR available for scanned or poor-quality PDFs. The project is designed to run entirely on local hardware without cloud dependencies and includes a web interface, satellite monitoring, proactive notifications, plugin hooks, and Paperless document-audit workflows. The repository describes more than 100 available tools and supports Docker-based self-hosting.

PI-Desktop is a local-first desktop workspace for AI coding agents, built with Electron, a Rust host core, and the pi Agent Harness. It lets users open local projects, connect cloud or local models through providers such as OpenAI-compatible APIs, manage projects and long-running sessions, and review file changes and command output. Its architecture separates the React renderer, Electron desktop orchestration, Rust-managed permissions, filesystem access, SQLite persistence and secrets, and a pi Agent sidecar responsible for the agent loop, model interaction, and streaming. Agent, Plan, and Goal modes provide different approval boundaries; agents can read and edit files, run commands, and delegate exploration, implementation, research, testing, or review to background Subagents. The workspace supports MCP servers, Skills, installable Plugins, model and provider switching, session imports, notifications, context checkpoints, and a plugin marketplace. Conversations are stored locally as JSONL with a SQLite index, settings and logs remain on the machine, credentials use the operating-system keychain, and model requests go directly to the configured provider or endpoint. Plugin processes are permission-gated and isolated from the renderer, but plugins remain user-trusted code rather than a complete operating-system sandbox. It is an early-preview cross-platform application distributed for macOS, Windows, and Linux under the GNU Lesser General Public License v3.0.

Pushary is a service for approving or authorizing AI agents from a mobile device when they pause to request permission. It supports agent frameworks and models including Claude Code, Codex, Cursor, and other MCP-compatible agents, allowing users to provide one-tap approvals so the agents can continue operating.