Your entire literature pile, searchable by what you remember

A working researcher’s reading is scattered by design: preprints on arXiv, published versions behind publisher pages, methods threads on blogs, conference talks on YouTube, and a “papers to read” folder that stopped being a system in 2023. The cost isn’t storage — it’s retrieval. You know you read a study whose control group design undermines the claim you’re reviewing, but reconstructing where you saw it eats half a morning.

Marqly treats your reading as one corpus. Save anything from the browser in one click, let AI tag and summarize it, mark up the passages that matter, and pull any of it back later by describing the idea rather than remembering the citation.

One library instead of five scattered ones

The first win is consolidation. Marqly’s extension saves from any page — publisher sites, preprint servers, blogs, news — and the side-panel library lets you browse and search your saves without leaving the page you’re reading. When a literature search leaves you with fifteen open tabs of candidate papers, the tab saver captures all of them at once instead of forcing a save-and-close ritual on each.

Two smaller capabilities quietly serve research habits as well. Save-as-PDF captures a page as a clean PDF matching the on-screen layout — processed locally in your browser — which preserves a blog post or news analysis exactly as it read on the day you cited it, even if the author edits it later. And the iOS app means the paper someone links in a group chat on Sunday still makes it into the corpus.

Every save is tagged automatically by AI, which matters more for researchers than for most people: your material genuinely spans topics, and manual taxonomy is exactly the kind of upkeep that collapses during a busy review cycle. How AI auto-tagging works explains what happens at save time; the practical effect is that “methods,” “replication,” and “grant writing” emerge as tags without you maintaining them.

Highlight passages and attach your commentary

Reading without annotating is half-reading. Marqly lets you highlight text on any website in six colors and attach notes — “effect size seems implausible given N,” “compare with the 2024 follow-up,” “quote this in the intro.” Highlights persist on the page when you return to a source, and they sync to your library as first-class objects.

That last part changes how annotations behave. In most workflows, marginalia die where you wrote them. In Marqly, your highlighted passages accumulate into a browsable, searchable record of what you found significant across the whole literature — closer to a running annotated bibliography than to scattered marks. Pair it with boards (one per project or paper-in-progress) and the raw material for a related-work section assembles itself as you read.

Search by concept, not by citation

Semantic search is the core of the product and the reason it fits research work. It matches meaning rather than keywords, across titles, full content, transcripts, and your own highlights. Queries that fail in every other tool work here: “the paper arguing pre-registration doesn’t reduce false positives,” “that talk where the speaker walked through the survey weighting problem.” The guide to searching bookmarks with AI shows the query patterns that work best.

Two supporting features round this out. AI summaries let you triage a backlog — twenty saved papers become twenty skimmable abstracts-of-abstracts, so you decide what deserves a deep read. And on Pro, chat with your saves answers questions from your own saved content: “which of my saved sources measured attrition directly?” is a question your library can now answer.

Video is literature now

Conference talks, methods tutorials, and recorded seminars carry real content that never appears in print. Marqly’s YouTube AI card gives every watch page a streaming summary with key sections, a playback-synced transcript with one-click copy, and a bookmark button that saves the video with its transcript attached — so a claim made at minute 43 of a keynote is as findable as a claim made in a PDF.

Getting started

1. Install the extension for Chrome, Edge, Firefox, or Safari from app.marqly.com — signup is free and needs no card.
2. Import your existing collections. Bring in browser bookmarks (the standard HTML export), a Pocket archive, or Raindrop.io collections in one pass.
3. Let auto-tagging process the backlog. The AI tags everything you imported, turning years of accumulated links into a structured library on day one. From there, the habit is one click per source, and the system in how to build a second brain maps well onto research practice.

Where Marqly is not the right tool: it is not a citation manager — it won’t format references or sync BibTeX, so keep Zotero or equivalent for bibliographies. There’s no offline mode, no public API for scripted pipelines, and no self-hosted option, which rules it out for air-gapped environments or institutions that require on-premise tools. If your bottleneck is recalling and reusing what you read — rather than formatting what you cite — that’s the job Marqly does well.