Spec Driven Development
by formulahendry
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Runs on your computer★ 440MITUpdated 14 months ago
Install
Mobster
Overview
Description from the maker (original English)
Control iPhones and iOS simulators: read screens, tap, type and verify. Requires macOS and uv.
PopNx MCP’s three pillars
These three are never merged into one score: opinions, measurements and popularity are different things.
- User voiceiNo reviews yetReviews open together with accounts in a later step
- Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
- UsageiNot measured yet★ –
What you can do with it
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
- Connection: Runs on your computer
- Transport: stdio
- Category: Other
Install
Pick the AI app you use, then copy the settings.
Before you install
- Basic checks: 1 of 1 passed
- Runs on your computer with your user’s permissions (files, network, apps).
- The registry lists no key to fill in.
You need
- PyPIPython’s uv installed (for the uvx command)
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"mobster": {
"command": "uvx",
"args": [
"mobster-cli",
"mcp"
]
}
}
}Run this in your terminal
claude mcp add mobster -- uvx mobster-cli mcpOr copy the settings yourself
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"mobster": {
"command": "uvx",
"args": [
"mobster-cli",
"mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Or copy the settings yourself
Paste into .vscode/mcp.json in your project
{
"servers": {
"mobster": {
"type": "stdio",
"command": "uvx",
"args": [
"mobster-cli",
"mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
Your choice stays on this device in a cookie; no account needed.
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
What it can do
Runs on your computer; the tool list appears in your AI app after you install it.
Basic checksi
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026
- ✓ Pass
Maker matches the repo
The registry name was verified against the domain mobster.dev (the registry checks domain ownership)
- … Not checked yet
Still maintained
We have not read this repo from GitHub yet
- … Not checked yet
Has a licence
We have not read this repo from GitHub yet
- – Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
- – Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
- … Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints
Compared with others in Otheri
- More stars than 0% of the other 32433 servers in this category
- Published to the registry more recently than 99% of the other 32433 servers in this category
- Basic checks equal to or better than 100% of the other 32433 servers in this category
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
Common questions
Is Mobster safe?
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
What keys or codes does it need?
The registry does not list a required key, though some servers ask you to sign in on first use.
Does it run on my computer or in the cloud?
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
Is it still maintained?
The GitHub repo last changed –, and the latest version (0.4.3) reached the registry today.
Which apps can use it?
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.
What can I use instead?
In the same category: Spec Driven Development, Remote Desktop Commander, Symantec Cloud DLP AIops
Alternatives
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Remote Desktop Commander
by desktop-commander
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Runs in the cloud★ 211Updated yesterday
Install
Symantec Cloud DLP AIops
by AIops-tools
Governed Symantec Cloud DLP — 14 MCP tools, read-only with audit.
Runs on your computerUpdated today
Install
README from the maker
Open the README
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
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
| Path | What it is |
|---|---|
mobile_agent/frontier.py | The loop: one model plans every step; the guards, the task contract and the DONE gate |
mobile_agent/contract.py | What the task asked for, and the proof on screen that each part was done |
mobile_agent/engines.py | The configuration the app and the benchmarks share (model, reasoning, limits), and the result summary |
mobile_agent/drivers.py, state.py | WebDriverAgent's HTTP API: the accessibility tree as a snapshot, then taps, typing and swipes |
mobile_agent/transport.py, gemini.py | The transport under the model calls. The Claude, OpenAI and Gemini clients and the price table are in model_clients.py |
mobile_agent/journal.py, task_policy.py, effect_ledger.py, secret_filter.py, system_dialogs.py, permissions/ | The safety core: the device lock and run journal, what counts as a send, buy, post or delete, the duplicate-action guard, secret masking, iOS's own prompts, the approval gate |
mobile_agent/harness_api.py | The seam to Mobster for Mac: registries and hooks, empty in this repository |
examples/reference_loop.py | The loop's API in the order a run uses it |
mobile_agent/bench/, mobile_agent/evals/ | MobsterBench-iOS, the iOSWorld harness, the baselines, the paired A/B tools, VisionJudge's labelled set |
mobile_agent/docs/, research/ | Design notes and dated research write-ups |
How one step works
- 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.
- 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.
- 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.
- 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 (
task_policy.py,permissions/), and an action whose outcome is unknown is never sent again (effect_ledger.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/.
| Measured | Result | Losses and gaps |
|---|---|---|
iOSWorld dev_core split, this loop on Claude Sonnet 5.5 at low reasoning, simulators, 10 to 11 Oct 2026 | 53.8% official pass; agent time p50 103 s; about $0.18 a task | Multi-app tasks pass 31%. The best published result, 51.9%, is on all 133 tasks, so the two aren't directly comparable |
| iOSWorld, 16 unseen tasks, paired A/B, 28 Sep 2026 | Sonnet 5.5 50% (95% CI 28 to 72), $0.197 a task; Opus 5.5 56% (31 to 81); gpt-5.6-sol 50% | No difference between the models is significant at this size |
| MobsterBench-iOS, 68 tasks, iPhone 15 Pro over USB, 24 Sep 2026 | 54 of 66 passed (82%, CI 71 to 89); p50 7.7 s a task; $0.0057 a task | Multi-app 2 of 6. One risky tap blocked and 2 unintended actions recorded. Not held out: fixes went in between passes (63%, 71%, 82%). No baseline ran |
| Where time goes, 346 runs, 22 Sep 2026 | The device side is about 61% of wall time, the model about 36% | At least 17% is waiting for the screen to settle |
| FrameClock (the MJPEG stream as a settle clock), iPhone 15 Pro, 23 Sep 2026 | Mean navigation settle 1,122 to 996 ms with 0 premature settles in 48 | 0 of 32 premature still allows up to about 9%; Safari's pixel settle isn't measured |
| VisionJudge on 135 labelled public-domain images, 23 Sep 2026 | 1 error in 117 answers (99.1% precision) | One rater; thresholds fitted on the same set; not phone screenshots |
| The action verifier, 34 attempts, 19 Sep 2026 | Correct actions allowed 14 of 14; wrong actions blocked 12 of 12 | It let through 6 actions it should have refused; repeating an Add is still unsolved |
The September results predate 13 Oct 2026, when this loop became Mobster's only engine. The October iOSWorld numbers are this loop. The research notes describe modules that ship in Mobster for Mac (the frame clock, hedged calls, skills); their code isn't in this repository.
Tests
The tests need no phone, simulator, network or key:
make venvmake test-backend
mobile_agent/tests/test_engine_boundary.py checks that the engine imports nothing outside its own modules, and runs the reference example on a scripted phone and model.
Third-party software
The engine installs jsonschema and referencing (MIT) and Pillow (MIT-CMU) from PyPI. It talks to WebDriverAgent (BSD-3-Clause, Facebook, Inc.) over HTTP; this repository holds none of its code. VisionJudge's images are CC0 or public domain, credited in mobile_agent/evals/vision/manifest.json.
License
MIT, copyright Radish Retail, LLC. See LICENSE. Report a vulnerability as SECURITY.md says.