@yubao2000/mcp-browser-agent
npm
v0.5.0
Published by @yubao2000 — no publish provenance, so origin is unverified, but the source is public: the repository link below is self-declared yet readable, so you can inspect the code before adopting it.
Lets AI agents operate a browser like a human, with around 30 tools including cookie persistence, PDF export, and tab management.
The grade answers one question — how safe is this server for you to adopt — so it is computed in two auditable stages. Nothing below is an opinion or an LLM's guess; every line is a real term the deterministic engine applied, and the same input always yields the same number.
1. Threat score — 100 − 0 = 100. What the published surface and source actually contain:
The deterministic scan raised no scored threat in the surface it inspected — the threat score stayed at 100. Capability observations and advisory notes are recorded but never lower it.
2. Client adoption risk — 100 − 4 = 96. Three small, subtract-only factors that reflect your risk in adopting it — a clean scan proves less on a powerful, unverified or barely-inspectable package, so the grade says so plainly:
| Points | Adoption-risk factor |
|---|---|
| −3 | capability blast radius (moderate) — client exposure if the model is manipulated |
| −1 | publisher verification (public source) — no provenance, but the source is public and inspectable |
Capability observations and info notes are shown under Findings but never scored.
Open any row's finding below for the file, line and evidence behind a deduction.
In the server's implementation (`dist/pro/license.js:44`): A hardcoded outbound call to a fixed external host inside server code is a classic exfiltration/telemetry channel — especially paired with reads of local data. This is read from the code itself — not from the tool description — so a poisoned server cannot hide it behind honest-looking metadata.
Evidence: const response = await fetch("https://api.lemonsqueezy.com/v1/licenses/validate", { method: "POST",
Fix: Review this call path: confirm it never receives unsanitized tool input, constrain it, or remove it. Treat a server whose code reaches these sinks as high-capability regardless of what its tools claim.
Location: server dist/pro/license.js
In the server's implementation (`src/pro/license.ts:67`): A hardcoded outbound call to a fixed external host inside server code is a classic exfiltration/telemetry channel — especially paired with reads of local data. This is read from the code itself — not from the tool description — so a poisoned server cannot hide it behind honest-looking metadata.
Evidence: const response = await fetch("https://api.lemonsqueezy.com/v1/licenses/validate", { method: "POST", heade
Fix: Review this call path: confirm it never receives unsanitized tool input, constrain it, or remove it. Treat a server whose code reaches these sinks as high-capability regardless of what its tools claim.
Location: server src/pro/license.ts
Each tool and what it can reach — statically extracted from the published source.
browser_backno sensitive capabilitybrowser_batchno sensitive capabilitybrowser_clearno sensitive capabilitybrowser_clickno sensitive capabilitybrowser_clickAtno sensitive capabilitybrowser_closeno sensitive capabilitybrowser_closeTabno sensitive capabilitybrowser_consoleno sensitive capabilitybrowser_deleteCookiesno sensitive capabilitybrowser_dragno sensitive capabilitybrowser_evaluateno sensitive capabilitybrowser_exportno sensitive capabilitybrowser_extractno sensitive capabilitybrowser_fillno sensitive capabilitybrowser_forwardno sensitive capabilitybrowser_getBoundsno sensitive capabilitybrowser_getCookiesno sensitive capabilitybrowser_getHTMLno sensitive capabilitybrowser_getTitleno sensitive capabilitybrowser_getUrlno sensitive capabilitybrowser_getViewportno sensitive capabilitybrowser_hoverno sensitive capabilitybrowser_iframeno sensitive capabilitybrowser_mouseMoveno sensitive capabilitybrowser_newTabno sensitive capabilitybrowser_pdfno sensitive capabilitybrowser_pressKeyno sensitive capabilitybrowser_reloadno sensitive capabilitybrowser_resetno sensitive capabilitybrowser_screenshotno sensitive capabilitybrowser_screenshotElementno sensitive capabilitybrowser_scrollno sensitive capabilitybrowser_selectno sensitive capabilitybrowser_submitno sensitive capabilitybrowser_switchTabno sensitive capabilitybrowser_waitno sensitive capabilityScan history per published version. The engine is deterministic — the same version always yields the same score, so a changed score means the package itself changed.
| Version | Score | Findings | Engine | Scanned |
|---|---|---|---|---|
v0.5.0 latest |
A 96/100 | 2 | 1.13.0 | 2026-08-25 |
Show this server's live Trust Score in your README, docs or website. The badge is served straight from the registry and updates automatically after every rescan — no API key needed. It links back to this page, so anyone who sees the grade can also read the findings behind it instead of taking a number on faith.
The score above is reproducible: the same package version always yields the same result. Run it locally or over the free API — no account, no LLM, fully deterministic.
npx mcptrustchecker scan @yubao2000/mcp-browser-agent --online
Independent packages implementing the same tool, scanned with the same engine. Compare all 2 side by side →
Model Context Protocol (MCP) server that integrates AgentQL data extraction capabilities.
Screenshot any URL or HTML as PNG/JPEG/WebP from your AI agent. Full-page, clean, no install.
MCP server for aria51 accessibility scanner
Bridge any browser web app to Claude Code via MCP
Browserbase’s official MCP server: cloud headless browsers for agents, with sessions and screenshots.
MCP server for AI web browser automation using Browserbase and Stagehand