Use Cases
What you can do with E2LLM MCP
Real examples. Each is one prompt — no selectors, no scripts, no prompt engineering. The AI figures it out because SiFR tells it what matters.
E2LLM runs in your browser with your sessions. AI accesses everything you can — government portals, corporate intranets, paid subscriptions, private forums. No cookie export, no session hijacking. Your browser, your identity.
Two modes: precision (one complex form, high stakes) and scale (hundreds of items, need synthesis).
"Go to my national insurance personal area. Find the form for updating bank details. Fill it with my new account number, verify the preview, but don't submit — let me review first."
Result: Agent navigated through SSO login (already authenticated in browser), found the correct form in a nested menu structure, filled 6 fields including a branch code lookup dropdown, reached the confirmation preview, and stopped for human review. The form used dynamic validation and AJAX-loaded field dependencies — transparent to the user.
Your sessionAuth wallsHigh stakes
"My forum post got 200+ replies overnight. Read all of them and give me a summary: who agrees, who disagrees, what are the main counterarguments, and which replies should I respond to first."
Result: Agent scrolled through paginated replies in an authenticated forum, processed 214 comments across 11 pages, identified 3 main camps of opinion, flagged 7 replies with specific technical objections worth addressing, and ranked them by engagement.
Private contentBulk synthesisPaginated
Complex portals, bureaucratic UIs, forms with unclear instructions. You don't need to understand the interface — just ask. AI reads the page structure, interprets what's expected, and can act on your behalf. Zero prompt engineering: describe what you need in plain language.
"I'm on this government portal and I have no idea what they want. What is this page asking me to do? What are my options?"
Result: Agent captured the page, identified it as a benefits eligibility form with 4 sections. Explained each in plain language: "Section 1 asks about household size for benefit tier calculation. Section 2 is income verification — upload a pay stub or authorize automated check. The Continue button is disabled until Section 1 is complete." User said "fill it based on what you know about me" — agent completed 3 of 4 sections from context and asked about the one it couldn't infer.
Zero prompt engPlain languageComplex UIs
SiFR operates on the DOM, not pixels. CJK characters, RTL scripts, Cyrillic, Thai — all native because text is extracted from rendered elements, not recognized from screenshots. Vision models degrade on dense scripts. Raw HTML drowns you in 600K tokens. SiFR gives you the bus schedule in 3KB.
"Find me a bus from Sokcho to Gangneung next Thursday morning. I need departure times, prices, and which terminal."
Result: Agent navigated a Korean intercity bus site (fully Korean UI), selected cities from cascading dropdowns (dynamic, AJAX-loaded options), set the date via a date picker, found 6 morning departures ₩6,600–₩9,800, identified the terminal, and presented results in English. Three levels of dynamic form interaction that break both screenshot-based and raw HTML approaches — handled transparently.
CJK nativeDynamic formsZero config
E2LLM sees all your open tabs across browsers. AI works across them — comparing options, cross-referencing sources, consolidating research. Open ChatGPT and Claude side by side, ask both the same question, see where they converge. Or have AI research alternatives and leave tabs open for your review.
"I need a project management tool for a 10-person team. Find 3 solid alternatives, open each in a tab, read their pricing and features, then give me a comparison. Leave the tabs open so I can look myself."
Result: Agent opened 3 competitor sites in separate tabs, navigated pricing and feature pages on each, extracted plan details, feature matrices, and integration lists. Produced a comparison table covering price per seat, storage, integrations, and mobile support. All tabs remained open for manual review. One prompt, 4 minutes, zero context-switching.
Cross-tabMulti-siteTabs stay open
You don't need a QA team to test your site. You don't need a webdev to check responsive layouts. Point AI at your staging URL and ask. One prompt, full audit — functional bugs, UX issues, i18n mistakes, style inconsistencies. The human perception bottleneck in web development is gone.
"Go to our staging site. Check every page. Find all bugs — functional, UX, i18n, and style inconsistencies. Write a report."
Result: 31 bugs found in one pass on a production SaaS app — 8 functional (including a GET instead of POST on file upload), 5 UX issues, 17 missing accents in localized text, 1 style inconsistency between forms. One prompt. Zero test scripts. The person who ran this was not a developer.
No QA teamFull auditOne prompt
Every website becomes usable — regardless of how it was built. SiFR reads what's actually rendered, not what the accessibility tree claims. AI acts on behalf of users who can't navigate complex UIs themselves.
Motor impairments: "fill this form and submit it." Visual impairments: "describe what's on screen and where things are." Cognitive barriers: "explain what this page wants me to do." Language barriers: "this is in a language I don't read — help me."
Not an audit tool. Not a compliance checkbox. An agent that gives people back their agency on the web.
"I can't use the mouse easily. I need to book a medical appointment on the clinic portal. Find available slots this week for Dr. Cohen, pick the earliest morning slot, and fill in my details."
Result: Agent navigated the booking system — dropdown menus, calendar picker, time slot grid, patient form with 12 fields. Completed the entire flow that would normally require precise mouse interaction and multi-step navigation. User confirmed the summary, agent submitted. One conversation, full autonomy, zero mouse interaction required.
Motor impairmentsCognitive barriersLanguage barriers