Official read-only MCP server for HackerOne bug bounty reports, programs, and remediation data.
Peekaboo
Summary
macOS screen capture and GUI automation over MCP — see the screen, then click, type and navigate it, with local or hosted vision models.
Features
- see: capture and annotate the screen before acting on it
- Full input and navigation set: click, type, hotkey, scroll, drag, window, space, dock
- Background input delivery that does not steal focus
- Local vision via Ollama or LM Studio, or hosted providers
- agent and run tools for multi-step and scripted workflows
Installation
Set up this MCP server in your favorite AI agent — copy a ready-made configuration below.
Description
Peekaboo is the macOS counterpart to the desktop-automation servers that exist for Windows: a CLI and MCP server that lets an agent take a real look at the screen and then act on it. The see tool captures and annotates the UI so the model knows what it is pointing at; everything after that is ordinary interaction — click, type, set-value, press, hotkey, paste.
Navigation and discovery are covered properly rather than as an afterthought: scroll, swipe, drag, move, plus window, space, app and dock for arranging the environment, and menu, menubar, dialog, screen and list for finding what is available without guessing coordinates. An agent tool takes a natural-language instruction and runs the multi-step flow itself, and run executes saved workflow scripts.
A detail that matters in practice: input can be delivered to a target process in the background, so automation does not have to steal focus from whatever you are doing. Vision can come from hosted providers (OpenAI, Anthropic, xAI, Google, MiniMax, Kimi) or from a local model through Ollama or LM Studio, so screenshots need not leave the machine.
Requires macOS 15 Sequoia or later, with Screen Recording and Accessibility permissions granted; the npm MCP server needs Node 22+. Published as @steipete/peekaboo, MIT licensed.
Related MCP Servers
A proxy that lets local-only MCP clients connect to remote servers, handling OAuth and transport differences.
Control Blender from an AI client — build scenes, apply materials, and run Python against the live session.
Run AI-generated code safely in an isolated cloud sandbox, with results returned as data rather than text.