Mobster MCP server

Mobster engine

The agent loop behind Mobster for Mac, and the research we measured it with. MIT.

An agent that drives your iPhone can read your messages and tap Send. This repository is the code that decides when: the observe, decide, verify, act loop, the WebDriverAgent driver it reads and acts through, and the safety core in front of every action. Next to it are the benchmarks, the evals and the results we published, with the losses printed next to the wins.

Mobster for Mac is the product built on this loop. It sets up your iPhone, shows it live, asks for your OK on a card, runs workflows on a schedule, adds itself to Claude Code, Cursor and Codex, and runs the loop with the speed and quality work that lives in the app. Get Mobster for Mac at mobster.dev.

Read the loop

How one step works

1. Observe. The driver reads the app's accessibility tree from WebDriverAgent and turns it into a snapshot: each element's role, label, value and frame.
2. Decide. The model gets the task, the plan so far and the screen as numbered rows, and answers with the next 1 to 6 actions.
3. Verify. Before an action goes out, the loop checks it against the screen it was chosen on. After it, the loop reads the screen again and checks the action took effect.
4. Act. The driver taps, types or swipes, and the loop goes back to step 1 until the contract's proof is on screen or a limit stops it.

Around every step, the safety core holds:

• The loop asks before a send, a buy, a post or a delete (taskpolicy.py, permissions/), and an action whose outcome is unknown is never sent again (effectledger.py).
• Every event is emitted before the next action is sent. Mobster for Mac writes each one to its journal (journal.py), and one run holds a phone's lock at a time.
• Passwords, one-time codes, card numbers and keys are masked before anything is stored (secret_filter.py).
• Text read from the phone is data. It never reaches the model as an instruction.

examples/reference_loop.py shows the API end to end on a fixed, read-only task: reading the iOS version in Settings. You bring a WebDriverAgent runner that serves your iPhone and a Claude or OpenAI key. It answers no to every approval.

Results

Every number names what was measured, on what, and when. The method and confidence intervals are in mobile_agent/docs/benchmarks.md and research/.

Shortened. The full README is on GitHub.