jev-browser

Browser automation where an LLM plans and Jev decides.

Unofficial project, not affiliated with TypeSafe. It calls the TypeSafe System One API with your own API key.

The calling LLM (Claude, via MCP) says what outcome it wants, one step at a time, and hands over any text to type. For each round of a step, code describes the page. Then one ~300 ms Typesafe System One request asks Jev several questions at once: which element, which action, which value, and is the step done / blocked / showing an error / about to do something irreversible. Playwright performs the action. The LLM never reads page snapshots unless it chooses to take over.

Claude ── browser_do("Log in", {email, password}) ──▶ jev-browser
                                                       │  loop until done / stuck / needs confirmation
                                                       │   1. settle   (network + DOM quiet)
                                                       │   2. describe (elements, labels, state, visible text, diff, counts)
                                                       │   3. Jev      (done? error? irreversible? tool? target? value?)
                                                       │   4. act      (Playwright)
Claude ◀── { status: "done", url, actions[], done_score } ─┘

Jev only answers with probability distributions: yes/no (noul), pick one option (choice) or a rating (score). It never writes text. So everything free-form comes from the caller as candidates, and code turns disagreement or low confidence into a status the LLM can act on.

42 tasks in 16 categories on live sites (see RESULTS.md):

• 40/42 correct in the latest run, 0 false "done" claims (38/41 twice before the latest fixes). Remaining misses: counting ("add until 3", flagged likely_done) and verifying a sort.
• ~300 ms per Jev call, 2–4 calls for most steps; a 5-step checkout takes ~14 s end to end.
• Pause before irreversible actions: across ~200 rounds it flagged only saucedemo's "Finish" (place order) button.
• Less page content for the LLM than a Playwright-MCP-style loop on the same tasks (estimate): median 5× per task, ≈8k vs ≈557k tokens in total. Big pages dominate the total: a Wikipedia article is ~149k snapshot tokens. On tiny pages there is no saving. The page reading moves to Jev.

Works on: forms, native and custom dropdowns, checkboxes and radios (including styled replacements), dynamic loading, modals, JS dialogs, hover, right-click, drag and drop, key presses, file upload, iframes, shadow DOM, new tabs, pages with 2,000+ elements (two-stage selection), and non-English UIs.

Known limits, so write steps around them:

• Ordered sub-goals in one step ("add two todos, complete one, clear completed") → split into one outcome per step.
• Open-ended goals ("scroll to load more") → make them measurable or check yourself.
• Judgements that compare many values (is this table sorted, did exactly one thing change) → verify with browser_check or browser_snapshot.

npx playwright install chromium          # once
claude mcp add jev-browser -e TYPESAFE_API_KEY=your-key -- npx -y -p jev-browser jev-browser-mcp

Any MCP client works the same way: command npx, args -y -p jev-browser jev-browser-mcp, env TYPESAFE_API_KEY. Add JEV_BROWSER_HEADED=1 to watch it work.

git clone https://github.com/Ying-Kai-Liao/jev-browser && cd jev-browser
npm install
npm run setup                    # downloads Chromium for Playwright
cp .env.example .env             # add TYPESAFE_API_KEY
npm test                         # offline tests (no network, no key)
npm run test:e2e                 # MCP server end to end (network + key)

claude mcp add jev-browser -- node /absolute/path/to/jev-browser/bin/jev-browser-mcp.mjs

From a source checkout the server reads TYPESAFE_API_KEY from the repo's .env.

browser_do statuses:

Env: JEV_BROWSER_HEADED=1 shows the browser, JEV_BROWSER_PROFILE=/dir keeps a persistent profile (logins survive restarts), JEV_BROWSER_LOG=1 prints per-round decisions to stderr.

// npm install jev-browser && npx playwright install chromium
import { JevBrowser } from "jev-browser";

const b = await JevBrowser.launch({ headed: true });
await b.open("https://www.saucedemo.com/");
await b.do("Log in", { values: { username: "standard_user", password: "secret_sauce" } });
await b.do("Add the Sauce Labs Backpack to the cart");
const p = await b.check("Does the cart badge show 1 item?");   // 0..1
await b.close();

node examples/x-profile-demo.mjs     # headed, read-only x.com walkthrough with decision highlights

Each action is outlined in red with Jev's choice and scores before it happens (highlight: true, on by default in the MCP server when JEV_BROWSER_HEADED=1). Some sites, x.com included, serve a blank page to headless Chromium: use headed mode there.

node bin/jev-browser.mjs do https://the-internet.herokuapp.com/login "Log in" username=tomsmith 'password=SuperSecretPassword!'
node bin/jev-browser.mjs run examples/flows/todomvc.json --headed

• One observable outcome per step: "Log in", "Open the Pull requests tab", "Mark 'buy milk' completed".
• Every string goes in values with a meaningful key (email, postal_code, file).
• Treat likely_done, needs_confirmation, ambiguous and stuck as your turn: check, snapshot or ask the user, don't just retry.
• After steps with side effects, browser_check what must not have changed.

node bench/run.mjs --set all            # base, hard, guard (+ bench/tasks.local.mjs if present)
node bench/run.mjs --only ti-login,drag
node bench/context-cost.mjs bench/results/<run>.json

Private sites and credentials go in bench/tasks.local.mjs (git-ignored), exporting LOCAL.

src/session.mjs      JevBrowser: settle, snapshot, decide (1 or 2 stages), resolve, act, do, check, choose
src/page-script.mjs  runs in each frame: elements, labels, state, visible text, metrics, dialogs
src/page-model.mjs   pure helpers: diff between pages, counts, compact rendering
src/jev.mjs          System One API client
src/flow.mjs         JSON flow runner
bin/                 CLI and MCP server
bench/               tasks with ground-truth checks, runner, context-cost estimate
test/                offline fixture tests, MCP end-to-end test
NOTES.md             design notes: what works with Jev, what doesn't, and why

CI runs the offline tests on every push and pull request. To publish, bump the version and push the tag; .github/workflows/release.yml tests, publishes to npm with provenance and creates a GitHub release:

npm version patch            # or minor / major: commits and tags vX.Y.Z
git push --follow-tags

Publishing uses npm trusted publishing, set up once with npx npm@latest trust github jev-browser --file release.yml --repo Ying-Kai-Liao/jev-browser --allow-publish.

MIT