Touchpoint

Give your AI agent eyes and hands on any desktop.

pip install touchpoint-py

AI agent researches data in Chrome, then creates a formatted Excel table — full task completed in ~12 minutes

Touchpoint is a cross-platform Python library for reading and interacting with desktop UI through native accessibility APIs. One import, one API — works on Linux, macOS, and Windows, with built-in support for Chromium and Electron apps via CDP (Chrome DevTools Protocol).

Instead of scraping pixels or running vision models, Touchpoint reads the real accessibility tree — structured names, roles, states, and positions for every element on screen. Fast and reliable, with no model inference needed. Ships with an MCP server so LLM agents like Claude or Cursor can control any desktop app out of the box.

import touchpoint as tp

elements = tp.find("Send", role=tp.Role.BUTTON, app="Slack")
tp.click(elements[0])

Why Touchpoint?

Table of Contents

• Table of Contents
• Install
  • Platform requirements
• Quick Start
  • Element IDs
  • Output formats
• MCP Server
  • Tools
  • Client setup
  • Environment variables
• Browser & Electron Apps (CDP)
  • Setup
• API Reference
  • Discovery
  • Search & Wait
  • Actions
  • Input
  • Screenshot & Config
• Architecture
• Configuration
• Development
• Status
  • Known limitations
• License

Install

Requires Python 3.10+.

pip install touchpoint-py

Everything is included: your platform's native backend, CDP support for browsers and Electron apps, the MCP server, and screenshot capabilities. Platform-specific dependencies are installed automatically via pip environment markers.

Platform requirements

Quick Start

import touchpoint as tp

# Discover
apps = tp.apps()                            # ["Firefox", "Slack", "Terminal", ...]
windows = tp.windows()                      # Window objects with title, position, size
all_els = tp.elements(app="Firefox", named_only=True)  # only elements with text labels

# Find
results = tp.find("Search", role=tp.Role.TEXT_FIELD, app="Firefox")

# Act
tp.set_value(results[0], "touchpoint python", replace=True)
tp.press_key("enter")
tp.hotkey("ctrl", "s")                      # keyboard shortcuts

# Wait for UI changes
tp.wait_for("results", app="Firefox", timeout=10)

# Screenshot
img = tp.screenshot()                       # full desktop → PIL.Image
img = tp.screenshot(app="Firefox")           # cropped to app window

Element IDs

Every element has a unique ID like atspi:1234:1:2.0 or cdp:9222:TID:4. Action functions accept either an Element object or a bare ID string — useful for storing references across steps:

results = tp.find("Send", max_results=1)
element_id = results[0].id                  # "atspi:1234:1:5.2"

# later...
tp.click(element_id)                        # works with just the string

Output formats

Control how results are returned:

tp.elements(app="Slack", format="flat")     # one compact line per element (best for LLMs)
tp.elements(app="Slack", format="tree")     # indented parent/child hierarchy
tp.elements(app="Slack", format="json")     # full JSON with all fields

MCP Server

Touchpoint ships an MCP (Model Context Protocol) server with 20 tools, ready for any MCP-compatible client. Use it to let LLM agents like Claude, Cursor, or Copilot control your desktop.

Tools

The MCP server includes built-in instructions that teach LLM agents how to work effectively — the orient → locate → act → verify loop, how to use find(), and how to recover from errors.

         ┌──────────┐
    ┌───▶│  ORIENT  │  screenshot · apps · windows
    │    └────┬─────┘
    │         ▼
    │    ┌──────────┐
    │    │  LOCATE  │  find · elements · get_element
    │    └────┬─────┘
    │         ▼
    │    ┌──────────┐
    │    │   ACT    │  click · set_value · type_text · press_key
    │    └────┬─────┘
    │         ▼
    │    ┌──────────┐
    │    │  VERIFY  │───▶ Done ✅
    │    └────┬─────┘
    │         │ not yet
    └─────────┘

Client setup

{
  "mcpServers": {
    "touchpoint": {
      "command": "touchpoint-mcp"
    }
  }
}

{
  "servers": {
    "touchpoint": {
      "command": "touchpoint-mcp"
    }
  }
}

{
  "mcpServers": {
    "touchpoint": {
      "command": "touchpoint-mcp"
    }
  }
}

{
  "mcpServers": {
    "touchpoint": {
      "command": "touchpoint-mcp"
    }
  }
}

claude mcp add touchpoint -- touchpoint-mcp

{
  "mcpServers": {
    "touchpoint": {
      "command": "touchpoint-mcp"
    }
  }
}

Environment variables

Browser & Electron Apps (CDP)

Native accessibility APIs return limited data for Electron and Chromium apps (Slack, Discord, VS Code, etc.). Touchpoint's CDP backend connects via Chrome DevTools Protocol to get the full web content.

Auto-discovery is enabled by default — Touchpoint automatically finds running browsers and Electron apps that were launched with a debug port. No manual configuration needed beyond launching the app with the flag.

Setup

1. Launch the app with a debug port:

# Linux
google-chrome --remote-debugging-port=9222 --user-data-dir=/tmp/tp-chrome

# macOS
open -na "Google Chrome" --args --remote-debugging-port=9222 --user-data-dir=/tmp/tp-chrome

# Windows
start chrome --remote-debugging-port=9222 --user-data-dir=%TEMP%\tp-chrome

2. Configure Touchpoint:

import touchpoint as tp

tp.configure(cdp_discover=True)             # auto-discover from running processes
# or
tp.configure(cdp_ports={"Google Chrome": 9222})  # explicit mapping

3. Control what you get with the source parameter:

tp.elements(app="Google Chrome", source="full")     # native chrome + web content (default)
tp.elements(app="Google Chrome", source="ax")       # web content only (CDP accessibility tree)
tp.elements(app="Google Chrome", source="native")   # native UI only (toolbar, tabs, menus)
tp.elements(app="Google Chrome", source="dom")      # DOM walker (catches what AX misses)

CDP results are merged with native backend results — you get the toolbar and window controls from AT-SPI2/UIA/AX, combined with the full web page content from CDP, in a single elements() call.

API Reference

Discovery

Search & Wait

Actions

Input

Screenshot & Config

All action functions accept an Element object or a string ID. elements(), find(), and get_element() support format="flat", format="json", or format="tree" (elements only) to return pre-formatted strings instead of objects.

Architecture

┌───────────────────────────────────────────────────────┐
│               import touchpoint as tp                 │
│  tp.find() · tp.click() · tp.screenshot() · ...       │
│                    (Public API)                       │
├─────────────────────────┬─────────────────────────────┤
│     Backend (ABC)       │    InputProvider (ABC)      │
├─────────────────────────┼─────────────────────────────┤
│  AT-SPI2     (Linux)    │  Xdotool       (X11)        │
│  UIA         (Windows)  │  SendInput     (Win32)      │
│  AX          (macOS)    │  CGEvent       (macOS)      │
│  CDP         (browsers) │                             │
├─────────────────────────┴─────────────────────────────┤
│  Utilities: formatter · matcher · screenshot · scale  │
└───────────────────────────────────────────────────────┘

Two-layer design:

• Backend reads the accessibility tree and runs structured actions (click, set_value, focus). Element-aware and reliable.
• InputProvider simulates raw keyboard and mouse input. Coordinate-based and element-blind. Used as an automatic fallback when a native accessibility action isn't available.

CDP runs alongside the platform backend. Their results are merged: native window chrome (toolbar, tabs, menus) from AT-SPI2/UIA/AX, plus full web content from CDP, unified under one API.

For detailed internals, see ARCHITECTURE.md.

Configuration

tp.configure(
    fuzzy_threshold=0.6,          # minimum match score for find() (0.0–1.0)
    fallback_input=True,          # use InputProvider when native actions fail
    type_chunk_size=40,           # split long text into chunks for typing (0 = disable)
    max_elements=5000,            # max elements per query
    max_depth=10,                 # default tree depth limit
    scale_factor=None,            # display scale override (None = auto-detect)
    cdp_ports={"Chrome": 9222},   # explicit CDP port mapping
    cdp_discover=True,            # auto-discover CDP ports from running processes
    cdp_refresh_interval=5.0,     # seconds between CDP target scans
)

Development

git clone https://github.com/Touchpoint-Labs/touchpoint.git
cd touchpoint
python -m venv .venv && source .venv/bin/activate
pip install -e ".[dev]"
pytest

Status

Alpha — fully functional and tested on all three platforms. The API may change before 1.0 based on user feedback.

Known limitations

• Wayland input — The Linux InputProvider uses xdotool, which requires X11. On pure Wayland (no XWayland), keyboard/mouse simulation is unavailable. The accessibility tree and native actions still work.

• Synchronous CDP — CDP calls block on WebSocket responses. JavaScript dialogs (alert, confirm, prompt) are auto-dismissed to prevent deadlocks. An async rewrite is planned.

• No browser navigation API — Touchpoint doesn't have built-in URL navigation. Agents can navigate by interacting with UI elements directly: find the address bar, type a URL, press Enter.

Roadmap

High Priority

• Async CDP architecture — non-blocking WebSocket, proper dialog queuing, concurrent multi-tab queries

Medium Priority

• Text selection tool — select text within an element by content (e.g. "select this word"), across all backends
• Window management tools — minimize, maximize, close, move, resize windows
• Backend role/state parity — close remaining role mapping gaps (especially UIA on Windows)
• Batch action tool — execute a sequence of actions in one call to reduce LLM round trips
• Wayland input backend — libei / xdg-desktop-portal RemoteDesktop when X11 isn't available

Lower Priority

• Tooltip and notification visibility
• Code organisation (split large files)
• Element caching

License

MIT